Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.0
2.1
Journals
Machines
Editor’s Choice
share announcement

Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Order results
Result details
Results per page
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
16 pages, 4408 KiB  
Article
Identifying Parametric Models Used to Estimate Track Irregularities of a High-Speed Railway
by Sunghoon Choi
Machines 2023, 11(1), 6; https://doi.org/10.3390/machines11010006 - 21 Dec 2022
Cited by 2 | Viewed by 1434
Abstract
This study aims to identify parametric models to estimate track irregularities in high-speed railways with simple acceleration measurements. The primary contribution of current research is the development of effective parametric models with smaller parameters. These parameters are derived from the measured data via [...] Read more.
This study aims to identify parametric models to estimate track irregularities in high-speed railways with simple acceleration measurements. The primary contribution of current research is the development of effective parametric models with smaller parameters. These parameters are derived from the measured data via a specialized track geometry inspection system. An adaptive Kalman filter algorithm, using the displacement estimated from the acceleration signals as the input and measured track irregularities as the output, is applied to obtain the model’s unknown parameters. These models are applied to acceleration measured from high-speed rail vehicles in operation, and track irregularities are estimated in spatial and wavelength domains. The estimated irregularities are compared to the track geometry inspection system’s results. Full article
(This article belongs to the Section Vehicle Engineering)
►▼ Show Figures

Figure 1

17 pages, 3476 KiB  
Article
A General Pose Recognition Method and Its Accuracy Analysis for 6-Axis External Fixation Mechanism Using Image Markers
by Sida Liu, Yimin Song, Binbin Lian and Tao Sun
Machines 2022, 10(12), 1234; https://doi.org/10.3390/machines10121234 - 16 Dec 2022
Viewed by 1881
Abstract
The 6-axis external fixation mechanism with Gough-Stewart configuration has been widely applied to the correction of long bone deformities in orthopedics. Pose recognition of the mechanism is essential for trajectory planning of bone correction, but is usually implemented by the surgeons’ experience, resulting [...] Read more.
The 6-axis external fixation mechanism with Gough-Stewart configuration has been widely applied to the correction of long bone deformities in orthopedics. Pose recognition of the mechanism is essential for trajectory planning of bone correction, but is usually implemented by the surgeons’ experience, resulting in a relatively low level of correction accuracy. This paper proposes a pose recognition method based on novel image markers, and implements accuracy analysis. Firstly, a pose description of the mechanism is established with several freely installed markers, and the layout of the markers is also parametrically described. Then, a pose recognition method is presented by identifying the orientation and position parameters using the markers. The recognition method is general in that it encompasses all possible marker layouts, and the recognition accuracy is investigated by analyzing variations in the marker layout. On this basis, layout principles for markers that achieve a desired recognition accuracy are established, and an error compensation strategy for precision improvement is provided. Finally, experiments were conducted. The results show that volume errors of pose recognition were 0.368 ± 0.130 mm and 0.151 ± 0.045°, and the correction accuracy of the fracture model after taking compensation was 0.214 ± 0.573 mm and −0.031 ± 0.161°, validating the feasibility and accuracy of the proposed methods. Full article
(This article belongs to the Special Issue Development and Applications of Parallel Robots)
►▼ Show Figures

Figure 1

17 pages, 2409 KiB  
Article
Indirect Estimation of Tire Pressure on Several Road Pavements via Interacting Multiple Model Approach
by Renato Brancati and Francesco Tufano
Machines 2022, 10(12), 1221; https://doi.org/10.3390/machines10121221 - 15 Dec 2022
Cited by 4 | Viewed by 2316
Abstract
Generally, tire deflation results in a decrease in both handling performance and tire lifetime, and in fuel consumption increment. Therefore, the real-time knowledge of the pressure is important. Direct approaches via pressure sensors mounted on the rim of each tire are not practical, [...] Read more.
Generally, tire deflation results in a decrease in both handling performance and tire lifetime, and in fuel consumption increment. Therefore, the real-time knowledge of the pressure is important. Direct approaches via pressure sensors mounted on the rim of each tire are not practical, due to technical and economic reasons. Cost-effective solutions with real-time estimation of tire pressure are generally less accurate and reliable than direct ones. Dynamical estimators based on a suspension model need road surface topology information to compute disturbances on the suspension system as an input, which is typically unknown. This paper proposes an innovative approach to estimate tire pressure indirectly, without actual road surface roughness information. A vertical suspension dynamic model is used to build several unscented Kalman filters, parametrised around different road surface topologies. These estimators are combined following the Interacting Multiple Model approach, which gives an acceptable estimation of tire stiffness through a weighted average obtained from a probabilistic model. A known linear static relationship between the tire stiffness and inflation pressure is utilized to indirectly estimate the tire inflation pressure. A Monte Carlo analysis has been performed on a wide range of driving scenarios and vehicle manoeuvres. The results of the estimation have been compared to those of a single unscented Kalman filter, in order to validate the effectiveness of the proposed solution and to highlight the improved performances in monitoring tire pressure. Full article
(This article belongs to the Special Issue Feature Review Papers on Trends and Challenges in Automotive Engineering)
►▼ Show Figures

Figure 1

21 pages, 12924 KiB  
Article
Sliding Mode Based Load Frequency Control and Power Smoothing of Power Systems with Wind and BESS Penetration
by Zhiwen Deng, Chang Xu, Zhihong Huo, Xingxing Han and Feifei Xue
Machines 2022, 10(12), 1225; https://doi.org/10.3390/machines10121225 - 15 Dec 2022
Cited by 7 | Viewed by 2133
Abstract
This study aims to maintain the frequency stability of the power system penetrated by wind power. Hence, a battery energy storage system (BESS) is applied to smooth the wind power output in power systems and to enhance their load frequency control (LFC) capacity. [...] Read more.
This study aims to maintain the frequency stability of the power system penetrated by wind power. Hence, a battery energy storage system (BESS) is applied to smooth the wind power output in power systems and to enhance their load frequency control (LFC) capacity. A novel comprehensive control framework is proposed for power systems integrated with wind farms and BESS based on an adaptive fuzzy super-twisting sliding mode control (AF-SSMC) method. Firstly, the sliding functions and control laws of subsystems are designed according to different relative degrees. Then, the super-twisting algorithm is applied to suppress the chattering of the sliding mode control law. Furthermore, an adaptive fuzzy control method is used to adjust the control gains online for better control performance of the controllers. The Lyapunov stability theory is employed to prove the asymptotic stability of the subsystems. The model of an interconnected thermal power system with wind and BESS penetration is also constructed for simulation analyses. The results indicate that the AF-SSMC method effectively reduces the chattering, and the proposed framework stabilizes the frequency of the power system under system uncertainties and external disturbances. Moreover, the wind farm and BESS combined system accurately tracks a reference power to reduce wind power fluctuations. Full article
(This article belongs to the Special Issue Optimization and Control of Distributed Energy Systems)
►▼ Show Figures

Figure 1

17 pages, 1566 KiB  
Article
View-Invariant Spatiotemporal Attentive Motion Planning and Control Network for Autonomous Vehicles
by Melese Ayalew, Shijie Zhou, Imran Memon, Md Belal Bin Heyat, Faijan Akhtar and Xiaojuan Zhang
Machines 2022, 10(12), 1193; https://doi.org/10.3390/machines10121193 - 9 Dec 2022
Cited by 2 | Viewed by 2208
Abstract
Autonomous driving vehicles (ADVs) are sleeping giant intelligent machines that perceive their environment and make driving decisions. Most existing ADSs are built as hand-engineered perception-planning-control pipelines. However, designing generalized handcrafted rules for autonomous driving in an urban environment is complex. An alternative approach [...] Read more.
Autonomous driving vehicles (ADVs) are sleeping giant intelligent machines that perceive their environment and make driving decisions. Most existing ADSs are built as hand-engineered perception-planning-control pipelines. However, designing generalized handcrafted rules for autonomous driving in an urban environment is complex. An alternative approach is imitation learning (IL) from human driving demonstrations. However, most previous studies on IL for autonomous driving face several critical challenges: (1) poor generalization ability toward the unseen environment due to distribution shift problems such as changes in driving views and weather conditions; (2) lack of interpretability; and (3) mostly trained to learn the single driving task. To address these challenges, we propose a view-invariant spatiotemporal attentive planning and control network for autonomous vehicles. The proposed method first extracts spatiotemporal representations from images of a front and top driving view sequence through attentive Siamese 3DResNet. Then, the maximum mean discrepancy loss (MMD) is employed to minimize spatiotemporal discrepancies between these driving views and produce an invariant spatiotemporal representation, which reduces domain shift due to view change. Finally, the multitasking learning (MTL) method is employed to jointly train trajectory planning and high-level control tasks based on learned representations and previous motions. Results of extensive experimental evaluations on a large autonomous driving dataset with various weather/lighting conditions verified that the proposed method is effective for feasible motion planning and control in autonomous vehicles. Full article
(This article belongs to the Special Issue Dynamics and Control of Autonomous Vehicles)
►▼ Show Figures

Figure 1

18 pages, 4198 KiB  
Article
Configuration Design and Optimal Energy Management for Coupled-Split Powertrain Tractor
by Haishi Dou, Hongqian Wei, Youtong Zhang and Qiang Ai
Machines 2022, 10(12), 1175; https://doi.org/10.3390/machines10121175 - 7 Dec 2022
Cited by 7 | Viewed by 2033
Abstract
High-power tractors are regarded as effective operation tools in agriculture, and plugin hybrid tractors have shown potential as agricultural machinery, due to their wide application in energy conservation. However, the allocation of the output power of the motors and engine is a challenging [...] Read more.
High-power tractors are regarded as effective operation tools in agriculture, and plugin hybrid tractors have shown potential as agricultural machinery, due to their wide application in energy conservation. However, the allocation of the output power of the motors and engine is a challenging task, given that the energy management strategy (EMS) is nonlinearly constrained. On the other hand, the structure of the continuous variable transmission (CVT) system is complicated, and affects the price of tractors. In this paper, a variable configuration of a tractor that could have the same performance as a complex CVT system is proposed. To address the EMS issues that have shown poor performance in real time, where the programming runs online, firstly a demand power prediction algorithm is proposed in a rotary tillage operation mode. Secondly, an equivalent fuel consumption minimization strategy (ECMS) is used to optimize the power distribution between the engine and the motors. In addition, the equivalent factor is optimized with an offline genetic algorithm. Thirdly, the equivalent factor is converted into a lookup table, and is used for an online power distribution with different driving mileages and state-of-charge (SOC). The simulation results indicate that the equivalent fuel consumption is reduced by 8.4% and extends the operating mileage of pure electric power. Furthermore, the error between the actual and forecasted demand power is less than 1%. The online EMS could improve the mileage of the tractor working cycle with a more feasible fuel economy based on demand power predictions. Full article
(This article belongs to the Topic Vehicle Dynamics and Control)
►▼ Show Figures

Figure 1

18 pages, 6438 KiB  
Article
Wind Turbine Blade Defect Detection Based on Acoustic Features and Small Sample Size
by Yuefan Zhu, Xiaoying Liu, Shen Li, Yanbin Wan and Qiaoqiao Cai
Machines 2022, 10(12), 1184; https://doi.org/10.3390/machines10121184 - 7 Dec 2022
Cited by 5 | Viewed by 3024
Abstract
Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defects cannot be repaired in [...] Read more.
Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defects cannot be repaired in time, the cracks evolve into larger fractures, which can lead to blade rupture. As such, in this study, we developed a remote non-contact online health monitoring and warning system for wind turbine blades based on acoustic features and artificial neural networks. Collecting a large number of wind turbine blade defect signals was challenging. To address this issue, we designed an acoustic detection method based on a small sample size. We employed the octave to extract defect information, and we used an artificial neural network based on model-agnostic meta-learning (MAML-ANN) for classification. We analyzed the influence of locations and compared the performance of MAML-ANN with that of traditional ANN. The experimental results showed that the accuracy of our method reached 94.1% when each class contained only 50 data; traditional ANN achieved an accuracy of only 85%. With MAML-ANN, the training is fast and the global optimal solution is automatic searched, and it can be expanded to situations with a large sample size. Full article
(This article belongs to the Special Issue Advances in Wind and Solar Energy Generation)
►▼ Show Figures

Figure 1

18 pages, 3250 KiB  
Article
Optimization Design of Automotive Body Stiffness Using a Boundary Hybrid Genetic Algorithm
by Haolong Zhong, Ting Xu, Jianglin Yang, Meng Sun and Fei Gao
Machines 2022, 10(12), 1171; https://doi.org/10.3390/machines10121171 - 6 Dec 2022
Cited by 3 | Viewed by 2013
Abstract
At the conceptual design stage, it is critical to use appropriate structural analysis and optimization methods. The thin-walled beam transfer matrix method (TBTMM) is adopted to establish the mathematical model of the simplified vehicle body-in-white (BIW) structure in this paper and compare it [...] Read more.
At the conceptual design stage, it is critical to use appropriate structural analysis and optimization methods. The thin-walled beam transfer matrix method (TBTMM) is adopted to establish the mathematical model of the simplified vehicle body-in-white (BIW) structure in this paper and compare it with the results of the finite element method (S-FEM) to verify the approach. In addition, on the basis of the boundary simulation genetic algorithm (BSGA) and local search procedure, a boundary hybrid genetic algorithm (BHGA) is proposed. BHGA is benchmarked on 20 test functions and is compared with current meta-heuristic algorithms to prove its effectiveness and universality. Finally, considering the bending and torsional stiffness constraints, BIW conceptual model is lightweight and designed with an optimizer. Full article
(This article belongs to the Section Vehicle Engineering)
►▼ Show Figures

Figure 1

24 pages, 12467 KiB  
Article
Stiffness-Performance-Based Redundant Motion Planning of a Hybrid Machining Robot
by Yuhao He, Fugui Xie, Xin-Jun Liu, Zenghui Xie, Huichan Zhao, Yi Yue and Mingwei Li
Machines 2022, 10(12), 1157; https://doi.org/10.3390/machines10121157 - 3 Dec 2022
Cited by 2 | Viewed by 1859
Abstract
Large-scale components usually have complex structures with high local stiffness, and the holes on them are required to be machined with high precision, which makes it important and challenging to study how to efficiently and precisely drill in the large-scale components. This article [...] Read more.
Large-scale components usually have complex structures with high local stiffness, and the holes on them are required to be machined with high precision, which makes it important and challenging to study how to efficiently and precisely drill in the large-scale components. This article presents mobile hybrid machining equipment that consists of a five-axis parallel module, a 2-degree-of-freedom (DoF) robotic, arm and an automated guide vehicle (AGV) connected in series. With the ability of wide-range positioning and precise local processing, it has potential advantages in the drilling processing of large-scale components. Stiffness is one of the most important performances for machining equipment, and it’s highly related to the its configuration. For the discussed equipment, the stiffness is determined by the two-stage-positioning hybrid machining robot, which comprises a five-axis parallel module and a two-DoF robotic arm. The redundant motion of the hybrid machining robot makes it possible to optimize its configuration by reasonably planning redundant motion. Therefore, a redundant motion-planning method based on stiffness performance is proposed. A kinematic analysis of the five-axis parallel module, the robotic arm, and the hybrid machining robot is carried out. A hybrid robot usually consists of several subsystems, and to take the compliance of each subsystem into consideration, the stiffness-modeling method for the hybrid robot with n subsystems connected in series is proposed. The stiffness model of the hybrid machining robot is established by using this method, and the variation of the stiffness magnitude has the same trend as that obtained by using FEA software. Stiffness magnitude and isotropy indices are proposed to evaluate the robot’s stiffness performance along the axis of the spindle and in the plane perpendicular to the axis of the spindle. The redundant motion of the hybrid machining robot is planned by maximizing the stiffness magnitude along the spindle axis, with priority to the stiffness isotropy index. Finally, the drilling experiment is carried out, and the results show that the relative error of the hole diameter obtained under the optimal configuration of the hybrid machining robot is 1.63%, which is smaller than those obtained under the other two configurations for comparison with relative errors of 3.75% and 3.50%, respectively. It proves the validity of the redundant motion-planning method. The proposed stiffness-modeling method and the stiffness-performance indices are also applicable to other hybrid machining robots. Full article
(This article belongs to the Special Issue Development and Applications of Parallel Robots)
►▼ Show Figures

Figure 1

16 pages, 5214 KiB  
Article
Comparative Analysis of Current and Voltage THD at Different Grid Powers for Powerful Active Front-End Rectifiers with Preprogrammed PWM
by Alexander S. Maklakov, Tao Jing and Alexander A. Nikolaev
Machines 2022, 10(12), 1139; https://doi.org/10.3390/machines10121139 - 1 Dec 2022
Cited by 4 | Viewed by 1898
Abstract
Preprogrammed pulse width modulation (PPWM) techniques are drawing a great deal of interest due to their strong harmonic performance. However, there have not yet been any systematic studies or elaboration of the influence of different grid powers on current and voltage THD using [...] Read more.
Preprogrammed pulse width modulation (PPWM) techniques are drawing a great deal of interest due to their strong harmonic performance. However, there have not yet been any systematic studies or elaboration of the influence of different grid powers on current and voltage THD using PPWM. Therefore, this article focuses on a comparative analysis of current and voltage THD in a system with a three-phase, three-level active front-end (AFE) at different grid powers by applying PPWM. A six-pulse electric drive power circuit and one laboratory measurement platform were designed and set up to achieve the above goals. The comparative results were calculated up to the 50th (THD50) and 100th (THD100) harmonics against the frequency of the PPWM, ranging between 150 Hz and 750 Hz. The grid power and AFE power ratio was between 30 and 230 under three different AFE-consumed currents. The experimental results were analyzed and compared, and they demonstrated for the first time how the grid power and AFE power ratio with different PPWM patterns can influence current and voltage THD. The research results suggest that it is necessary to review the existing calculation methods for current and voltage THD using modern electric power quality standards. The results presented in this article also provide a reference point for researchers and engineers when considering the electromagnetic compatibility (EMC) of nonlinear consumers in the design of similar circuits. Full article
►▼ Show Figures

Figure 1

17 pages, 22611 KiB  
Article
A Novel Deep Learning-Based Pose Estimation Method for Robotic Grasping of Axisymmetric Bodies in Industrial Stacked Scenarios
by Yaowei Li, Fei Guo, Miaotian Zhang, Shuangfu Suo, Qi An, Jinlin Li and Yang Wang
Machines 2022, 10(12), 1141; https://doi.org/10.3390/machines10121141 - 1 Dec 2022
Cited by 2 | Viewed by 1610
Abstract
A vision-based intelligent robotic grasping system is essential for realizing unmanned operations in industrial manufacturing, and pose estimation plays an import role in this system. In this study, deep learning was used to obtain the 6D pose of an axisymmetric body which was [...] Read more.
A vision-based intelligent robotic grasping system is essential for realizing unmanned operations in industrial manufacturing, and pose estimation plays an import role in this system. In this study, deep learning was used to obtain the 6D pose of an axisymmetric body which was optimal for robotic grasping in industrial stacked scenarios. We propose a method to obtain the 6D pose of an axisymmetric body by detecting the pre-defined keypoints on the side surface. To realize this method and solve other challenges in industrial stacked scenarios, we propose a multitask real-time convolutional neural network (CNN), named Key-Yolact, which involves object detection, instance segmentation, and multiobject 2D keypoint detection. A small CNN as a decision-making subsystem was designed to score multiple predictions of Key-Yolact, and the body with the highest score is considered the best for grasping. Experiments on a self-built stacked dataset showed that Key-Yolact has a practical tradeoff between inference speed and precision. The inference speed of Key-Yolact is higher by 10 FPS, whereas its precision is decreased by only 7% when compared with the classical multitask Keypoint R-CNN. Robotic grasping experiments showed that the proposed design is effective and can be directly applied to industrial scenarios. Full article
(This article belongs to the Section Automation and Control Systems)
►▼ Show Figures

Figure 1

19 pages, 10024 KiB  
Article
Design and Control of a Lower Limb Rehabilitation Robot Based on Human Motion Intention Recognition with Multi-Source Sensor Information
by Pengfei Zhang, Xueshan Gao, Mingda Miao and Peng Zhao
Machines 2022, 10(12), 1125; https://doi.org/10.3390/machines10121125 - 28 Nov 2022
Cited by 5 | Viewed by 3118
Abstract
The research on rehabilitation robots is gradually moving toward combining human intention recognition with control strategies to stimulate user involvement. In order to enhance the interactive performance between the robot and the human body, we propose a machine-learning-based human motion intention recognition algorithm [...] Read more.
The research on rehabilitation robots is gradually moving toward combining human intention recognition with control strategies to stimulate user involvement. In order to enhance the interactive performance between the robot and the human body, we propose a machine-learning-based human motion intention recognition algorithm using sensor information such as force, displacement and wheel speed. The proposed system uses the bi-directional long short-term memory (BILSTM) algorithm to recognize actions such as falling, walking, and turning, of which the accuracy rate has reached 99.61%. In addition, a radial basis function neural network adaptive sliding mode controller (RBFNNASMC) is proposed to track and control the patient’s behavioral intention and the gait of the lower limb exoskeleton and to adjust the weights of the RBF network using the adaptive law. This can achieve a dynamic estimation of the human–robot interaction forces and external disturbances, and it gives the exoskeleton joint motor a suitable driving torque. The stability of the controller is demonstrated using the Lyapunov stability theory. Finally, the experimental results demonstrate that the BILSTM classifier has more accurate recognition than the conventional classifier, and the real-time performance can meet the demand of the control cycle. Meanwhile, the RBFNNASMC controller has a better gait tracking effect compared with the PID controller. Full article
(This article belongs to the Section Automation and Control Systems)
►▼ Show Figures

Figure 1

19 pages, 7410 KiB  
Article
Real-Time NMPC for Speed Planning of Connected Hybrid Electric Vehicles
by Fei Ju, Yuhua Zong, Weichao Zhuang, Qun Wang and Liangmo Wang
Machines 2022, 10(12), 1129; https://doi.org/10.3390/machines10121129 - 28 Nov 2022
Cited by 4 | Viewed by 1496
Abstract
Eco-cruising is considered an effective approach for reducing energy consumption of connected vehicles. Most eco-cruising controllers (ECs) do not comply with real-time implementation requirements when a short sampling interval is required. This paper presents a solution to this problem. Model predictive control (MPC) [...] Read more.
Eco-cruising is considered an effective approach for reducing energy consumption of connected vehicles. Most eco-cruising controllers (ECs) do not comply with real-time implementation requirements when a short sampling interval is required. This paper presents a solution to this problem. Model predictive control (MPC) framework was applied to the speed-planning problem for a power-split hybrid electric vehicle (HEV). To overcome the limitations of time-domain MPC (TMPC), a nonlinear space-domain MPC (SMPC) was proposed in the space domain. A real-time iteration (RTI) algorithm was developed to accelerate nonlinear SMPC computations via generating warm initializations and subsequently forming the SMPC-RTI. Proposed speed controllers were evaluated in a hierarchical EC, where a heuristic energy management strategy was selected for powertrain control. Simulation results indicated that the proposed SMPC yields comparable fuel savings to the TMPC and the globally optimal solution. Meanwhile, SMPC reduced MPC computation time by 41% compared to TMPC, and SMPC-RTI further reduced MPC computation time without compromising optimization. During the hardware-in-loop (HIL) test, the mean computation time was 9.86 ms, demonstrating potential for real-time applications. Full article
(This article belongs to the Special Issue Energy Management and ECO-Driving Strategies of Hybrid Electric Vehicles)
►▼ Show Figures

Figure 1

36 pages, 16046 KiB  
Review
Vibration Image Representations for Fault Diagnosis of Rotating Machines: A Review
by Hosameldin Osman Abdallah Ahmed and Asoke Kumar Nandi
Machines 2022, 10(12), 1113; https://doi.org/10.3390/machines10121113 - 23 Nov 2022
Cited by 12 | Viewed by 4768
Abstract
Rotating machine vibration signals typically represent a large collection of responses from various sources in a machine, along with some background noise. This makes it challenging to precisely utilise the collected vibration signals for machine fault diagnosis. Much of the research in this [...] Read more.
Rotating machine vibration signals typically represent a large collection of responses from various sources in a machine, along with some background noise. This makes it challenging to precisely utilise the collected vibration signals for machine fault diagnosis. Much of the research in this area has focused on computing certain features of the original vibration signal in the time domain, frequency domain, and time–frequency domain, which can sufficiently describe the signal in essence. Yet, computing useful features from noisy fault signals, including measurement errors, needs expert prior knowledge and human labour. The past two decades have seen rapid developments in the application of feature-learning or representation-learning techniques that can automatically learn representations of time series vibration datasets to address this problem. These include supervised learning techniques with known data classes and unsupervised learning or clustering techniques with data classes or class boundaries that are not obtainable. More recent developments in the field of computer vision have led to a renewed interest in transforming the 1D time series vibration signal into a 2D image, which can often offer discriminative descriptions of vibration signals. Several forms of features can be learned from the vibration images, including shape, colour, texture, pixel intensity, etc. Given its high performance in fault diagnosis, the image representation of vibration signals is receiving growing attention from researchers. In this paper, we review the works associated with vibration image representation-based fault detection and diagnosis for rotating machines in order to chart the progress in this field. We present the first comprehensive survey of this topic by summarising and categorising existing vibration image representation techniques based on their characteristics and the processing domain of the vibration signal. In addition, we also analyse the application of these techniques in rotating machine fault detection and classification. Finally, we briefly outline future research directions based on the reviewed works. Full article
(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Fault Diagnosis and Prognosis)
►▼ Show Figures

Figure 1

22 pages, 4490 KiB  
Review
Fiber Optic Fiber Bragg Grating Sensing for Monitoring and Testing of Electric Machinery: Current State of the Art and Outlook
by Asep Andi Suryandi, Nur Sarma, Anees Mohammed, Vidyadhar Peesapati and Siniša Djurović
Machines 2022, 10(11), 1103; https://doi.org/10.3390/machines10111103 - 21 Nov 2022
Cited by 20 | Viewed by 3472
Abstract
This paper presents a review of the recent trends and the current state of the art in the application of fiber optic fiber Bragg gratings (FBG) sensing technology to condition the monitoring (CM) and testing of practical electric machinery and the associated power [...] Read more.
This paper presents a review of the recent trends and the current state of the art in the application of fiber optic fiber Bragg gratings (FBG) sensing technology to condition the monitoring (CM) and testing of practical electric machinery and the associated power equipment. FBG technology has received considerable interest in this field in recent years, with research demonstrating that the flexible, multi-physical, and electromagnetic interference (EMI) immune in situ sensing of a multitude of physical measurands of CM interest is possible and cannot be obtained through conventional sensing means. The unique FBG sensing ability has the potential to unlock many of the electric machine CM and design validation restrictions imposed by the limitations of conventional sensing techniques but needs further research to attain wider adoption. This paper first presents the fundamental principles of FBG sensing. This is followed by a description of recent FBG sensing techniques proposed for electric machinery and associated power equipment and a discussion of their individual benefits and limitations. Finally, an outlook for the further application of this technique is presented. The underlying intention is for the review to provide an up-to-date overview of the state of the art in this area and inform future developments in FBG sensing in electric machinery. Full article
(This article belongs to the Special Issue Machine Health Diagnosis & Prognosis by Advanced Sensing and Data Driven Techniques)
►▼ Show Figures

Figure 1

15 pages, 7130 KiB  
Article
In Situ Ultrasonic Testing for Wire Arc Additive Manufacturing Applications
by Ana Beatriz Lopez, José Pedro Sousa, João P. M. Pragana, Ivo M. F. Bragança, Telmo G. Santos and Carlos M. A. Silva
Machines 2022, 10(11), 1069; https://doi.org/10.3390/machines10111069 - 12 Nov 2022
Cited by 5 | Viewed by 2970
Abstract
In this paper, we present a non-destructive testing (NDT) technique based on in situ detection of defects up to 100 °C by ultrasonic testing (UT) during construction of parts by a metal additive manufacturing technology known as wire arc additive manufacturing (WAAM). The [...] Read more.
In this paper, we present a non-destructive testing (NDT) technique based on in situ detection of defects up to 100 °C by ultrasonic testing (UT) during construction of parts by a metal additive manufacturing technology known as wire arc additive manufacturing (WAAM). The proposed technique makes use of interlayer application of commercial solder flux to serve as coupling medium for in situ inspection using a special-purpose UT probe. The experimental work was carried out in deposited ER5356 aluminum straight walls following a threefold structure. First, characterization tests with geometrically similar walls with and without interlayer application of solder flux highlight its neutrality, with no effect on the chemical, metallurgical and mechanical properties of the walls. Secondly, UT tests on walls at temperatures ranging from room temperature to 100 °C demonstrate the satisfactory performance of the solder flux as a coupling medium, with little to no soundwave amplitude losses or noise. Finally, acoustic attenuation, impedance and transmission estimations highlight the effectiveness of the proposed technique, establishing a basis for the future development of automated NDT systems for in situ UT of additive manufacturing processes. Full article
(This article belongs to the Special Issue Design for Additive Manufacturing: Engineering Data and Assessment Tools)
►▼ Show Figures

Figure 1

20 pages, 4347 KiB  
Article
Research on Energy Consumption Generation Method of Fuel Cell Vehicles: Based on Naturalistic Driving Data Mining
by Yangyang Ma, Pengyu Wang, Bin Li and Jianhua Li
Machines 2022, 10(11), 1047; https://doi.org/10.3390/machines10111047 - 9 Nov 2022
Cited by 1 | Viewed by 1694
Abstract
In this paper, an energy consumption generation method is proposed to accurately calculate the energy consumption of fuel cell vehicles (FCVs). A specific driver drives on a route (from Jilin University to FAW Volkswagen) for 331 working days (1 April 2020 to 28 [...] Read more.
In this paper, an energy consumption generation method is proposed to accurately calculate the energy consumption of fuel cell vehicles (FCVs). A specific driver drives on a route (from Jilin University to FAW Volkswagen) for 331 working days (1 April 2020 to 28 July 2021) and collects more than 40,000 s of naturalistic driving data by means of a GPS receiver (FRII-D). To accurately calculate the energy consumption data of FCVs under actual driving cycles, naturalistic driving data mining is first studied. The principal component analysis (PCA) algorithm is used to reduce the dimension of the extracted driving cycle characteristic parameters, the K-means algorithm is used for driving cycle clustering, and the LVQ is used for driving cycle identification. Then, the characteristic parameters correlated to energy consumption are obtained based on the FCV model and regression analysis method. In addition, an energy consumption generation method is designed and proposed based on the characteristic parameters and identification results. Furthermore, the proposed energy consumption generation method can accurately calculate the energy consumption of FCVs, which also provides a reference for further research on the efficient energy management of FCVs. Full article
(This article belongs to the Special Issue Emerging Technologies in New Energy Vehicle)
►▼ Show Figures

Figure 1

17 pages, 5529 KiB  
Article
A GAN-BPNN-Based Surface Roughness Measurement Method for Robotic Grinding
by Guojun Zhang, Changyuan Liu, Kang Min, Hong Liu and Fenglei Ni
Machines 2022, 10(11), 1026; https://doi.org/10.3390/machines10111026 - 4 Nov 2022
Cited by 6 | Viewed by 2382
Abstract
Existing machine vision-based roughness measurement methods cannot accurately measure the roughness of free-form surfaces (with large curvature variations). To overcome this problem, this paper proposes a roughness measurement method based on a generative adversarial network (GAN) and a BP neural network. Firstly, this [...] Read more.
Existing machine vision-based roughness measurement methods cannot accurately measure the roughness of free-form surfaces (with large curvature variations). To overcome this problem, this paper proposes a roughness measurement method based on a generative adversarial network (GAN) and a BP neural network. Firstly, this method takes images and curvature of free-form surfaces as training samples. Then, GAN is trained for roughness measurement through each game between generator and discriminant network by using real samples and pseudosamples (from generator). Finally, the BP neural network maps the image discriminant value of GAN and radius of curvature into roughness value (Ra). Our proposed method automatically learns the features in the image by GAN, omitting the independent feature extraction step, and improves the measurement accuracy by BP neural network. The experiments show that the accuracy of the proposed roughness measurement method can measure free-form surfaces with a minimum roughness of 0.2 μm, and measurement results have a margin of 10%. Full article
(This article belongs to the Special Issue Industrial Process Improvement by Automation and Robotics)
►▼ Show Figures

Figure 1

27 pages, 9687 KiB  
Article
Variable Dimensional Scaling Method: A Novel Method for Path Planning and Inverse Kinematics
by Longfei Jia, Zhiyuan Yu, Haiping Zhou, Zhe Pan, Yangsheng Ou, Yaxing Guo and Yuping Huang
Machines 2022, 10(11), 1030; https://doi.org/10.3390/machines10111030 - 4 Nov 2022
Cited by 4 | Viewed by 1588
Abstract
Traditional methods for solving the inverse kinematics of a hyper-redundant manipulator (HRM) can only plan the path of the end-effector with a complicated solving process, where obstacle avoidance is also not considered. To solve the above problems, a novel method for solving inverse [...] Read more.
Traditional methods for solving the inverse kinematics of a hyper-redundant manipulator (HRM) can only plan the path of the end-effector with a complicated solving process, where obstacle avoidance is also not considered. To solve the above problems, a novel method for solving inverse kinematics of HRM is proposed in this paper: the variable dimension scaling method (VDSM), which can solve complex inverse kinematics while avoiding obstacles. Through this method, the path of the end-effector is scaled under a certain proportion and is adjusted depending on the position of the obstacle, which has good universality. The number of link angles changed is as small as possible in the process of achieving the end-effector moving along the desired path. With the redundancy of HRM, obstacle avoidance can be implemented in any environment by the proposed method. Through simulation and experiments in different environments, the above advantages of VDSM are verified. Full article
(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)
►▼ Show Figures

Figure 1

21 pages, 7231 KiB  
Article
Early Fault Warning Method of Wind Turbine Main Transmission System Based on SCADA and CMS Data
by Huanguo Chen, Jie Chen, Juchuan Dai, Hanyu Tao and Xutao Wang
Machines 2022, 10(11), 1018; https://doi.org/10.3390/machines10111018 - 2 Nov 2022
Cited by 3 | Viewed by 2325
Abstract
The main transmission system of wind turbines is a multi-component coupling system, and its operational state is complex and varied. These lead to frequent false alarms and missed alarms in existing monitoring systems. To accurately obtain the operational state of the main transmission [...] Read more.
The main transmission system of wind turbines is a multi-component coupling system, and its operational state is complex and varied. These lead to frequent false alarms and missed alarms in existing monitoring systems. To accurately obtain the operational state of the main transmission system and detect its abnormal operation, an early fault warning method for the main transmission system based on SCADA and CMS data is proposed. Firstly, the SCADA and CMS feature parameters relevant to the operating status of the main transmission system are selected by two different methods separately, and the correlation mechanism between the feature parameters and the operating characteristics of the main transmission system is further analyzed. Secondly, the Long Short-Term Memory (LSTM) network-based prediction model of the main transmission system operating parameters is established, in which SCADA and CMS feature parameters are fused as the input feature vectors. Then, the predicted residuals of the state evaluation parameters are used as the operational state evaluation index. The early fault warning model is established by Analytic Hierarchy Process (AHP) and Kernel Density Estimation (KDE). Finally, a case study is used to verify the correct performance of the proposed method. The results show that this method can realize early warning functions 73 h earlier than the existing SCADA system. The method can provide a theoretical basis for the safe operation and condition-based maintenance of wind turbines. Full article
(This article belongs to the Special Issue Wind Turbine Technologies)
►▼ Show Figures

Figure 1

21 pages, 3965 KiB  
Article
Geometric Error Analysis of a 2UPR-RPU Over-Constrained Parallel Manipulator
by Xu Du, Bin Wang and Junqiang Zheng
Machines 2022, 10(11), 990; https://doi.org/10.3390/machines10110990 - 29 Oct 2022
Cited by 7 | Viewed by 1682
Abstract
For a 2UPR-RPU over-constrained parallel manipulator, some geometric errors result in internal forces and deformations, which limit the improvement of the pose accuracy of the moving platform and shorten the service life of the manipulator. Analysis of these geometric errors is important for [...] Read more.
For a 2UPR-RPU over-constrained parallel manipulator, some geometric errors result in internal forces and deformations, which limit the improvement of the pose accuracy of the moving platform and shorten the service life of the manipulator. Analysis of these geometric errors is important for restricting them. In this study, an evaluation model is established to analyse the influence of geometric errors on the limbs’ comprehensive deformations for this manipulator. Firstly, the nominal inverse and actual forward kinematics are analysed according to the vector theory and the local product of the exponential formula. Secondly, the evaluation model of the limbs’ comprehensive deformations is established based on kinematics. Thirdly, 41 geometric errors causing internal forces and deformations are identified and the results are verified through simulations based on the evaluation model. Next, two global sensitivity indices are proposed and a sensitivity analysis is conducted using the Monte Carlo method throughout the reachable workspace of the manipulator. The results of the sensitivity analysis indicate that 10 geometric errors have no effects on the average angular comprehensive deformation and that the identified geometric errors have greater effects on the average linear comprehensive deformation. Therefore, the distribution of the global sensitivity index of the average linear comprehensive deformation is more meaningful for accuracy synthesis. Finally, simulations are performed to verify the results of sensitivity analysis. Full article
(This article belongs to the Special Issue New Frontiers in Parallel Robots)
►▼ Show Figures

Figure 1

21 pages, 5085 KiB  
Article
Federated Multi-Model Transfer Learning-Based Fault Diagnosis with Peer-to-Peer Network for Wind Turbine Cluster
by Wanqian Yang and Gang Yu
Machines 2022, 10(11), 972; https://doi.org/10.3390/machines10110972 - 24 Oct 2022
Cited by 6 | Viewed by 2138
Abstract
Intelligent fault diagnosis for a single wind turbine is hindered by the lack of sufficient useful data, while multi-turbines have various faults, resulting in complex distributions. Collaborative intelligence can better solve these problems. Therefore, a peer-to-peer network is constructed with one node corresponding [...] Read more.
Intelligent fault diagnosis for a single wind turbine is hindered by the lack of sufficient useful data, while multi-turbines have various faults, resulting in complex distributions. Collaborative intelligence can better solve these problems. Therefore, a peer-to-peer network is constructed with one node corresponding to one wind turbine in a cluster. Each node is equivalent and functional replicable with a new federated transfer learning method, including model transfer based on multi-task learning and model fusion based on dynamic adaptive weight adjustment. Models with convolutional neural networks are trained locally and transmitted among the nodes. A solution for the processes of data management, information transmission, model transfer and fusion is provided. Experiments are conducted on a fault signal testing bed and bearing dataset of Case Western Reserve University. The results show the excellent performance of the method for fault diagnosis of a gearbox in a wind turbine cluster. Full article
(This article belongs to the Special Issue Machine Learning for Fault Diagnosis of Wind Turbines)
►▼ Show Figures

Figure 1

31 pages, 4118 KiB  
Review
Intelligent Mechatronics in the Measurement, Identification, and Control of Water Level Systems: A Review and Experiment
by Paweł Olejnik and Jan Awrejcewicz
Machines 2022, 10(10), 960; https://doi.org/10.3390/machines10100960 - 20 Oct 2022
Cited by 4 | Viewed by 4297
Abstract
In this paper, a unique overview of intelligent machines and mathematical methods designed and developed to measure and to control the water level in industrial or laboratory setups of coupled and cascaded configurations of tanks is made. A systematized and concise overview is [...] Read more.
In this paper, a unique overview of intelligent machines and mathematical methods designed and developed to measure and to control the water level in industrial or laboratory setups of coupled and cascaded configurations of tanks is made. A systematized and concise overview is made of the mechatronic systems used in the measurement, identification, and control of the water level enumerates, the software used in the associated scientific research, modern techniques and sensors, and mathematical models, as well as analysis and control strategies. The broad overview of applications of the last decade is finalized by a proposition of a control system that is based on a parameter estimation of a new experimental setup, an integral dynamic model of the system, a modern mechatronic machine such as the Watson-Marlow peristaltic pump, the Anderson Negele sensor of level, the NI cRIO-9074 controller, and LabVIEW virtual instrumentation. The results of real experimental tests, exploiting a hybrid proportional control, being improved by a numerically predicted water level, are obtained using a few tools, i.e., the static characteristics, the classical step response, and a new pyramid-shaped step function of a discontinuous path-following reference input, being introduced to evaluate the effectiveness and robustness of the regulation of the level height. Full article
(This article belongs to the Special Issue Feature Review Papers on Automation Systems)
►▼ Show Figures

Figure 1

20 pages, 4363 KiB  
Article
Shape Accuracy Improvement in Selective Laser-Melted Ti6Al4V Cylindrical Parts by Sliding Friction Diamond Burnishing
by Gyula Varga, Gergely Dezső and Ferenc Szigeti
Machines 2022, 10(10), 949; https://doi.org/10.3390/machines10100949 - 19 Oct 2022
Cited by 2 | Viewed by 1556
Abstract
Additively manufactured metallic parts usually need postprocessing in order to achieve required shape accuracy. Cylindrical test specimens were produced by selective laser melting from Ti6Al4V powder material with different processing parameters. The aim of postprocessing was modification of shape accuracy. Sliding friction diamond [...] Read more.
Additively manufactured metallic parts usually need postprocessing in order to achieve required shape accuracy. Cylindrical test specimens were produced by selective laser melting from Ti6Al4V powder material with different processing parameters. The aim of postprocessing was modification of shape accuracy. Sliding friction diamond burnishing was applied as the postprocessing method. A five-factor, two-level full factorial design of experiment was implemented with factors being infill laser power, infill laser scan speed, burnishing speed, feed and force. Improvement ratios of two roundness parameters were defined, calculated from experimental data, and studied by main effect and interaction analysis. It has been demonstrated that burnishing feed has the largest main effect to improvement in roundness total and cylindricity. Additionally, parameters of both selective laser melting and diamond burnishing appear in three largest interaction terms. Empirical functions were fit to measurement data. Results show that improvement in roundness parameters are strongly nonlinear functions of all factors. Full article
(This article belongs to the Special Issue Additive Manufacturing of Machine Components)
►▼ Show Figures

Figure 1

16 pages, 3240 KiB  
Article
Teaching Motion Control in Mechatronics Education Using an Open Framework Based on the Elevator Model
by Filippo Sanfilippo, Martin Økter, Tine Eie and Morten Ottestad
Machines 2022, 10(10), 945; https://doi.org/10.3390/machines10100945 - 18 Oct 2022
Cited by 5 | Viewed by 2923
Abstract
Universities and other educational institutions may find it difficult to afford the cost of obtaining cutting-edge teaching resources. This study introduces the adoption of a novel open prototyping framework in the context of mechatronics education, employing low-cost commercial off-the-shelf (COTS) components and tools [...] Read more.
Universities and other educational institutions may find it difficult to afford the cost of obtaining cutting-edge teaching resources. This study introduces the adoption of a novel open prototyping framework in the context of mechatronics education, employing low-cost commercial off-the-shelf (COTS) components and tools for the motion control module. The goal of this study is to propose a novel structure for the motion control module in the engineering mechatronics curriculum. The objective is to foster a new teaching method. From a methodology perspective, students are involved in a series of well-organised theoretical lectures as well as practical, very engaging group projects in the lab. To help students understand, draw connections, and broaden their knowledge, the methods of surface learning and deep learning are frequently mixed thoroughly. The structure of the course as well as the key topics are discussed. The proposed open framework, which consists of an elevator model, is presented in details. Students’ early evaluation indicates that the course organisation and subjects are successful and beneficial. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
►▼ Show Figures

Figure 1

21 pages, 10163 KiB  
Article
Developing and Testing the Proto Type Structure for Micro Tool Fabrication
by Hang Xiao, Xiaolong Hu, Shaoqing Luo and Wei Li
Machines 2022, 10(10), 938; https://doi.org/10.3390/machines10100938 - 16 Oct 2022
Cited by 1 | Viewed by 1763
Abstract
Compared with traditional machine tools, the micro machine tools have advantages of small volume, low cost, less energy consumption, high efficiency and high flexibility. Therefore, it is regarded as an important equipment for micro-cutting machining which has been used widely all over the [...] Read more.
Compared with traditional machine tools, the micro machine tools have advantages of small volume, low cost, less energy consumption, high efficiency and high flexibility. Therefore, it is regarded as an important equipment for micro-cutting machining which has been used widely all over the world and. As a key component of the micro-cutting machine tools, the body structure directly influences the machining performance. Thus, an integral column and base structure for micro machining tools was proposed in this work, and the detailed structural parameters were designed based on parameter analysis. Besides, the static and dynamic performance of the proposed machine were analyzed and compared between the integral structure and the separated one. The deformation and stress of the proposed structures under typical working conditions were studied by numerical simulation, along with the natural frequencies, vibration modes and frequency response peaks. Further, optimization was performed on the integral body structure, the prototype of the micro-machine tool was trial-produced, and the positioning accuracy of each coordinate axis was qualitatively analyzed. In addition, the micro-milling test was carried out with 6061 aluminum alloy to show the performance of the novel cutting machine. The results revealed that the proposed integrated micro-machine bed structure is superior to the separated structure in terms of static deformation and harmonic response characteristics, with good comprehensive mechanical properties, greatly improved static and dynamic performance of the machine tool, significantly improved structural accuracy, improved processing quality of the specimen and good application value. Full article
(This article belongs to the Special Issue High Precision Abrasive Machining: Machines, Processes and Systems)
►▼ Show Figures

Figure 1

25 pages, 6861 KiB  
Article
Morphing Wing Based on Trigonal Bipyramidal Tensegrity Structure and Parallel Mechanism
by Jian Sun, Xiangkun Li, Yundou Xu, Tianyue Pu, Jiantao Yao and Yongsheng Zhao
Machines 2022, 10(10), 930; https://doi.org/10.3390/machines10100930 - 13 Oct 2022
Cited by 3 | Viewed by 2304
Abstract
The development of morphing wings is in the pursuit of lighter weight, higher stiffness and strength, and better flexible morphing ability. A structure that can be used as both the bearing structure and the morphing mechanism is the optimal choice for the morphing [...] Read more.
The development of morphing wings is in the pursuit of lighter weight, higher stiffness and strength, and better flexible morphing ability. A structure that can be used as both the bearing structure and the morphing mechanism is the optimal choice for the morphing wing. A morphing wing composed of a tensegrity structure and a non-overconstrained parallel mechanism was designed. The self-balancing trigonal bipyramidal tensegrity structure was designed based on the shape-finding method and force-equilibrium equation of nodes. The 4SPS-RS parallel mechanism that can complete wing morphing was designed based on the configuration synthesis method. The degree of freedom and inverse solution of the parallel mechanism was obtained based on the screw theory, and the Jacobian matrix of the parallel mechanism was established. The stiffness model of the tensegrity structure and the 4SPS-RS parallel mechanism was established. The relationship between the deformation of the 4SPS-RS parallel mechanism and sweep angle, torsion angle, spanwise bending, and span was obtained. Through the modular assembly and distributed drive, the morphing wing could perform smooth and continuous morphing locally and globally. In the static state, it has the advantages of high stiffness and large bearing capacity. In the process of morphing, it can complete morphing motion with four degrees of freedom in changing sweep, twist, spanwise bending, and span of the wing. Full article
(This article belongs to the Special Issue Development and Applications of Parallel Robots)
►▼ Show Figures

Figure 1

18 pages, 4431 KiB  
Article
A Robust and Efficient UAV Path Planning Approach for Tracking Agile Targets in Complex Environments
by Shunfeng Cui, Yiyang Chen and Xinlin Li
Machines 2022, 10(10), 931; https://doi.org/10.3390/machines10100931 - 13 Oct 2022
Cited by 13 | Viewed by 2320
Abstract
The research into the tracking methods of unmanned aerial vehicles (UAVs) for agile targets is multi-disciplinary, with important application scenarios. Using a quadrotor as an example, in this paper, we mainly researched the tracking-related modeling and application verification of agile targets. We propose [...] Read more.
The research into the tracking methods of unmanned aerial vehicles (UAVs) for agile targets is multi-disciplinary, with important application scenarios. Using a quadrotor as an example, in this paper, we mainly researched the tracking-related modeling and application verification of agile targets. We propose a robust and efficient UAV path planning approach for tracking agile targets aggressively and safely. This approach comprehensively takes into account the historical observations of the tracking target and the surrounding environment of the location. It reliably predicts a short time horizon position of the moving target with respect to the dynamic constraints. Firstly, via leveraging the Bernstein basis polynomial and combining obstacle distribution information around the target, the prediction module evaluated the future movement of the target, presuming that it endeavored to stay away from the obstacles. Then, a target-informed dynamic searching method was embraced as the front end, which heuristically searched for a safe tracking trajectory. Secondly, the back-end optimizer ameliorated it into a spatial–temporal optimal and collision-free trajectory. Finally, the tracking trajectory planner generated smooth, dynamically feasible, and collision-free polynomial trajectories in milliseconds, which is consequently reasonable for online target tracking with a restricted detecting range. Statistical analysis, simulation, and benchmark comparisons show that the proposed method has at least 40% superior accuracy compared to the leading methods in the field and advanced capabilities for tracking agile targets. Full article
(This article belongs to the Special Issue Advanced Data Analytics in Intelligent Industry: Theory and Practice)
►▼ Show Figures

Figure 1

23 pages, 1232 KiB  
Article
Optimal Design of Axial Flux Permanent Magnet Motors for Ship RIM-Driven Thruster
by Hichem Ouldhamrane, Jean-Frédéric Charpentier, Farid Khoucha, Abdelhalim Zaoui, Yahia Achour and Mohamed Benbouzid
Machines 2022, 10(10), 932; https://doi.org/10.3390/machines10100932 - 13 Oct 2022
Cited by 4 | Viewed by 5358
Abstract
This paper deals with the design and optimization of a 2.1 MW rim-driven electric thruster for ship propulsion. For this purpose, a double stator ironless rotor axial flux permanent magnet (AFPM) motor is considered as the propulsion motor. The analytical model of the [...] Read more.
This paper deals with the design and optimization of a 2.1 MW rim-driven electric thruster for ship propulsion. For this purpose, a double stator ironless rotor axial flux permanent magnet (AFPM) motor is considered as the propulsion motor. The analytical model of the selected AFPM motor is presented. The magnetic field in the AFPM machine is calculated using the 3D magnetic charge concept in combination with image theory and permeance functions to take into account the stator slotting effects, and a simple thermal model is used to evaluate the heat dissipation capabilities of the machine and the thermal dependence of the main electromagnetic losses. To optimally design the AFPM, an optimization process based on genetic algorithms is applied to minimize the cost of the active motor materials. An appropriate objective function has been constructed, and different constraints related to the main electrical, geometrical, and mechanical parameters have been taken into account. The achieved results are compared with the performance of a podded radial flux permanent magnet (RFPM) motor, which is considered a reference propulsion motor. The obtained results show a fairly satisfactory improvement in the cost and masses of the active motor materials. Finally, the accuracy of the obtained optimum solution is validated by performing 3D finite element analysis (3D-FEA) simulations. Full article
(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Electrical Machines and Drives)
►▼ Show Figures

Figure 1

18 pages, 24450 KiB  
Article
Taikobot: A Full-Size and Free-Flying Humanoid Robot for Intravehicular Astronaut Assistance and Spacecraft Housekeeping
by Qi Zhang, Cheng Zhao, Li Fan and Yulin Zhang
Machines 2022, 10(10), 933; https://doi.org/10.3390/machines10100933 - 13 Oct 2022
Cited by 5 | Viewed by 4331
Abstract
This paper proposes a full-size and free-flying humanoid robot named Taikobot that aims to assist astronauts in a space station and maintain spacecrafts between human visits. Taikobot adopts a compact and lightweight (∼25 kg) design to work in microgravity, which also reduces launch [...] Read more.
This paper proposes a full-size and free-flying humanoid robot named Taikobot that aims to assist astronauts in a space station and maintain spacecrafts between human visits. Taikobot adopts a compact and lightweight (∼25 kg) design to work in microgravity, which also reduces launch costs and improves safety during human–robot collaboration. Taikobot’s anthropomorphic dual arm system and zero-g legs allow it to share a set of intravehicular human–machine interfaces. Unlike ground-walking robots, Taikobot maneuvers in a novel push–flight–park (PFP) strategy as an equivalent astronaut in a space station to maximize workspace and flexibility. We propose a PFP motion planning and control method based on centroidal dynamics and multi-contact model. Based on the proposed method, we carried out extensive simulations and verified the feasibility and advantages of the novel locomotion strategy. We also developed a prototype of Taikobot and carried out several ground experiments on typical scenarios where the robot collaborates with human astronauts. The experiments show that Taikobot can do some simple and repetitive tasks along with astronauts and has the potential to help astronauts improve their onboard working efficiency. Full article
(This article belongs to the Topic Intelligent Systems and Robotics)
►▼ Show Figures

Figure 1

13 pages, 1741 KiB  
Article
A Lower Limb Rehabilitation Robot with Rigid-Flexible Characteristics and Multi-Mode Exercises
by Mingjie Dong, Jianping Yuan and Jianfeng Li
Machines 2022, 10(10), 918; https://doi.org/10.3390/machines10100918 - 10 Oct 2022
Cited by 7 | Viewed by 2526
Abstract
Lower limb rehabilitation robot (LLRR) can effectively help restore the lower limb’s motor function of patients with hemiplegia caused by stroke through a large number of targeted and repetitive rehabilitation training. To improve the safety and comfort of robot-assisted lower limb rehabilitation, we [...] Read more.
Lower limb rehabilitation robot (LLRR) can effectively help restore the lower limb’s motor function of patients with hemiplegia caused by stroke through a large number of targeted and repetitive rehabilitation training. To improve the safety and comfort of robot-assisted lower limb rehabilitation, we developed an LLRR with rigid-flexible characteristics; the design of passive joints is used to improve human-machine compatibility; the design of flexible unit makes the mechanism have certain rigid-flexible characteristics. Three different rehabilitation training methods have been developed to adapt to the patients at different stages of rehabilitation, namely, passive exercise, active exercise and resistance exercise, respectively. Experiments with healthy subjects have been conducted to verify the effectiveness of the development of the different training modes of the LLRR, showing good compatibility of the mechanism and good trajectory tracking performance of the developed training methods. Full article
(This article belongs to the Section Automation and Control Systems)
►▼ Show Figures

Figure 1

15 pages, 5561 KiB  
Article
Machining Performance for Ultrasonic-Assisted Magnetic Abrasive Finishing of a Titanium Alloy: A Comparison with Magnetic Abrasive Finishing
by Fujian Ma, Ziguang Wang, Yu Liu, Zhihua Sha and Shengfang Zhang
Machines 2022, 10(10), 902; https://doi.org/10.3390/machines10100902 - 6 Oct 2022
Cited by 6 | Viewed by 1991
Abstract
Titanium alloys are widely used in aerospace, the military industry, electronics, automotive fields, etc., due to their excellent properties such as low density, high strength, high-temperature resistance, and corrosion resistance. Many components need to be finished precisely after being cut in these applications. [...] Read more.
Titanium alloys are widely used in aerospace, the military industry, electronics, automotive fields, etc., due to their excellent properties such as low density, high strength, high-temperature resistance, and corrosion resistance. Many components need to be finished precisely after being cut in these applications. In order to achieve high-quality and high-efficiency finishing of titanium alloys, ultrasonic-assisted magnetic abrasive finishing (UAMAF) was introduced in this research. The machining performance for UAMAF of a titanium alloy was studied by experimentally comparing UAMAF and magnetic abrasive finishing (MAF). The results show that the cutting force of UAMAF can reach 2 to 4 times that of MAF, and it decreases rapidly with the increase in the machining gap due to the energy loss of ultrasonic impact in the transmission between magnetic abrasives. The surface roughness of UAMAF can reach about Ra 0.075 μm, which is reduced by about 59% compared with MAF. The main wear type of the magnetic abrasive is that the diamond grits fell off the magnetic abrasive in both UAMAF and MAF. The uniform wear of the magnetic abrasive is realized, and the utilization ratio of the magnetic abrasive is obviously improved in UAMAF. Full article
(This article belongs to the Special Issue High Precision Abrasive Machining: Machines, Processes and Systems)
►▼ Show Figures

Figure 1

17 pages, 4316 KiB  
Article
Experimental Study on the Influence of Micro-Abrasive and Micro-Jet Impact on the Natural Frequency of Materials under Ultrasonic Cavitation
by Tianjiao Song, Xijing Zhu, Linzheng Ye and Jing Zhao
Machines 2022, 10(10), 891; https://doi.org/10.3390/machines10100891 - 3 Oct 2022
Cited by 1 | Viewed by 1578
Abstract
The higher the natural frequency of the material is, the more resistant it is to deformation under impulse loading. To explore the influence of micro-abrasive and micro-jet impact on the natural frequency and resonance amplitude value of the material under ultrasonic cavitation, 18 [...] Read more.
The higher the natural frequency of the material is, the more resistant it is to deformation under impulse loading. To explore the influence of micro-abrasive and micro-jet impact on the natural frequency and resonance amplitude value of the material under ultrasonic cavitation, 18 sets of single-factor controlled variable ultrasonic cavitation experiments were carried out on a polished specimen of 6061 aluminum alloy (30 mm × 30 mm × 10 mm). With the increase of the abrasive content in the suspension, the natural frequency of the workpiece first increased, then decreased and remained stable. With the increase of the ultrasonic amplitude, the resonance amplitude value of the material increased, reaching the maximum at 0.1789 m·s−2 and then decreased. The effect of ultrasonic amplitude on the natural frequency of the material was greater than that of the abrasive content, and the effect of the abrasive content on the common amplitude value was greater than that of the ultrasonic amplitude. This research provides a certain reference significance for exploring the influence of power ultrasonic micro-cutting on material properties and avoiding the occurrence of resonance phenomenon of the workpiece under different working conditions. Full article
(This article belongs to the Section Advanced Manufacturing)
►▼ Show Figures

Figure 1

26 pages, 31851 KiB  
Article
Robust Tracking and Clean Background Dense Reconstruction for RGB-D SLAM in a Dynamic Indoor Environment
by Fengbo Zhu, Shunyi Zheng, Xia Huang and Xiqi Wang
Machines 2022, 10(10), 892; https://doi.org/10.3390/machines10100892 - 3 Oct 2022
Cited by 1 | Viewed by 1703
Abstract
This article proposes a two-stage simultaneous localization and mapping (SLAM) method based on using the red green blue-depth (RGB-D) camera in dynamic environments, which can not only improve tracking robustness and trajectory accuracy but also reconstruct a clean and dense static background model [...] Read more.
This article proposes a two-stage simultaneous localization and mapping (SLAM) method based on using the red green blue-depth (RGB-D) camera in dynamic environments, which can not only improve tracking robustness and trajectory accuracy but also reconstruct a clean and dense static background model in dynamic environments. In the first stage, to accurately exclude the interference of features in the dynamic region from the tracking, the dynamic object mask is extracted by Mask-RCNN and optimized by using the connected component analysis method and a reference frame-based method. Then, the feature points, lines, and planes in the nondynamic object area are used to construct an optimization model to improve the tracking accuracy and robustness. After the tracking is completed, the mask is further optimized by the multiview projection method. In the second stage, to accurately obtain the pending area, which contains the dynamic object area and the newly added area in each frame, a method is proposed, which is based on a ray-casting algorithm and fully uses the result of the first stage. To extract the static region from the pending region, this paper designs divisible and indivisible regions process methods and the bounding box tracking method. Then, the extracted static regions are merged into the map using the truncated signed distance function method. Finally, the clean static background model is obtained. Our methods have been verified on public datasets and real scenes. The results show that the presented methods achieve comparable or better trajectory accuracy and the best robustness, and can construct a clean static background model in a dynamic scene. Full article
(This article belongs to the Special Issue Advances in Mobile Robot Navigation in an Unstructured and Dynamically Cluttered Environment)
►▼ Show Figures

Figure 1

14 pages, 5271 KiB  
Article
Tool Remaining Useful Life Prediction Method Based on Multi-Sensor Fusion under Variable Working Conditions
by Qingqing Huang, Chunyan Qian, Chao Li, Yan Han, Yan Zhang and Haofei Xie
Machines 2022, 10(10), 884; https://doi.org/10.3390/machines10100884 - 1 Oct 2022
Cited by 3 | Viewed by 1745
Abstract
Under variable working conditions, the tool status signal is affected by changing machine processing parameters, resulting in a decreased prediction accuracy of the remaining useful life (RUL). Aiming at this problem, a method based on multi-sensor fusion for tool RUL prediction was proposed. [...] Read more.
Under variable working conditions, the tool status signal is affected by changing machine processing parameters, resulting in a decreased prediction accuracy of the remaining useful life (RUL). Aiming at this problem, a method based on multi-sensor fusion for tool RUL prediction was proposed. Firstly, the factorization machine (FM) was used to extract the nonlinear processing features in the low-frequency condition signal, and the one-dimensional separable convolution was applied to extract tool life state features from multi-channel high-frequency sensor signals. Secondly, the residual attention mechanism was introduced to weight the low-frequency condition characteristics and high-frequency state characteristics, respectively. Finally, the features extracted in the low-frequency and high-frequency parts were input into the full connection layer to integrate working condition information and state information to suppress the influence of variable conditions and improve prediction accuracy. The experimental results demonstrated that the method could predict the remaining life of the tool effectively, and the accuracy and stability of the model are better than several other methods. Full article
(This article belongs to the Section Advanced Manufacturing)
►▼ Show Figures

Figure 1

20 pages, 2151 KiB  
Article
Dynamic Response in Multiphase Electric Drives: Control Performance and Influencing Factors
by Angel Gonzalez-Prieto, Ignacio González-Prieto, Mario J. Duran and Juan J. Aciego
Machines 2022, 10(10), 866; https://doi.org/10.3390/machines10100866 - 27 Sep 2022
Cited by 5 | Viewed by 2045
Abstract
Speed variable electric drives play a key role in the evolution of electrical mobility. The dynamic performance of these systems is a crucial feature for security purposes. For this reason, a large number of works are focused on identification of the most appropriate [...] Read more.
Speed variable electric drives play a key role in the evolution of electrical mobility. The dynamic performance of these systems is a crucial feature for security purposes. For this reason, a large number of works are focused on identification of the most appropriate control technique to satisfy a transient scenario. In this regard, the dynamic abilities of linear and direct controllers were analysed for three-phase drives. Although some insights about their transient performance were obtained, there are yet some issues to be solved. For instance, speed response was typically omitted, some influencing factors were neglected or the multiphase case was carried out. Considering this information, this work proposes a comparative analysis of the dynamic performance of the most popular regulation strategies for a six-phase electric drive. This study analyses speed, current and voltage responses to achieve an overall view of the system performance. Two concepts were employed to simplify the comprehension of the dynamic behavior of a regulation strategy: reaction time and response capacity. Experimental results are employed to confirm the impact of the different agents on a transient situation. Full article
(This article belongs to the Special Issue Innovative Applications of Multiphase Machines)
►▼ Show Figures

Figure 1

17 pages, 3439 KiB  
Article
Uncertainty Quantification for Full-Flight Data Based Engine Fault Detection with Neural Networks
by Matthias Weiss, Stephan Staudacher, Jürgen Mathes, Duilio Becchio and Christian Keller
Machines 2022, 10(10), 846; https://doi.org/10.3390/machines10100846 - 23 Sep 2022
Cited by 5 | Viewed by 2456
Abstract
Current state-of-the-art engine condition monitoring is based on a minimum of one steady-state data point per flight. Due to the scarcity of available data points, there are difficulties distinguishing between random scatter and an underlying fault introducing a detection latency of several flights. [...] Read more.
Current state-of-the-art engine condition monitoring is based on a minimum of one steady-state data point per flight. Due to the scarcity of available data points, there are difficulties distinguishing between random scatter and an underlying fault introducing a detection latency of several flights. Today’s increased availability of data acquisition hardware in modern aircraft provides continuously sampled in-flight measurements, so-called full-flight data. These full-flight data give access to sufficient data points to detect faults within a single flight, significantly improving the availability and safety of aircraft. Artificial neural networks are considered well suited for the timely analysis of an extensive amount of incoming data. This article proposes uncertainty quantification for artificial neural networks, leading to more reliable and robust fault detection. An existing approach for approximating the aleatoric uncertainty was extended by an Out-of-Distribution Detection in order to take the epistemic uncertainty into account. The method was statistically evaluated, and a grid search was performed to evaluate optimal parameter combinations maximizing the true positive detection rates. All test cases were derived based on in-flight measurements of a commercially operated regional jet. Especially when requiring low false positive detection rates, the true positive detections could be improved 2.8 times while improving response times by approximately 6.9 compared to methods only accounting for the aleatoric uncertainty. Full article
(This article belongs to the Special Issue Diagnostics and Optimization of Gas Turbine)
►▼ Show Figures

Figure 1

19 pages, 5826 KiB  
Article
Signal Processing of Acoustic Data for Condition Monitoring of an Aircraft Ignition System
by Umair Ahmed, Fakhre Ali and Ian Jennions
Machines 2022, 10(9), 822; https://doi.org/10.3390/machines10090822 - 19 Sep 2022
Cited by 2 | Viewed by 3253
Abstract
Degradation of the ignition system can result in startup failure in an aircraft’s auxiliary power unit. In this paper, a novel acoustics-based solution that can enable condition monitoring of an APU ignition system was proposed. In order to support the implementation of this [...] Read more.
Degradation of the ignition system can result in startup failure in an aircraft’s auxiliary power unit. In this paper, a novel acoustics-based solution that can enable condition monitoring of an APU ignition system was proposed. In order to support the implementation of this research study, the experimental data set from Cranfield University’s Boeing 737-400 aircraft was utilized. The overall execution of the approach comprised background noise suppression, estimation of the spark repetition frequency and its fluctuation, spark event segmentation, and feature extraction, in order to monitor the state of the ignition system. The methodology successfully demonstrated the usefulness of the approach in terms of detecting inconsistencies in the behavior of the ignition exciter, as well as detecting trends in the degradation of spark acoustic characteristics. The identified features proved to be robust against non-stationary background noise, and were also found to be independent of the acoustic path between the igniter and microphone locations, qualifying an acoustics-based approach to be practically viable. Full article
(This article belongs to the Special Issue Fault Detection, Diagnosis and Prognostics of Machines: Applications and Advances)
►▼ Show Figures

Figure 1

18 pages, 16665 KiB  
Article
Design and Optimization of the Surface Texture at the Hydrostatic Bearing and the Spindle for High Precision Machining
by Youyun Shang, Kai Cheng, Hui Ding and Shijin Chen
Machines 2022, 10(9), 806; https://doi.org/10.3390/machines10090806 - 13 Sep 2022
Cited by 7 | Viewed by 2282
Abstract
Hydrostatic bearing spindles are widely applied in high precision grinding and turning machines due to their good dynamic stability and rotational accuracy. However, under the condition of high-speed rotations, the heat generated by the friction of the oil film will cause the shear [...] Read more.
Hydrostatic bearing spindles are widely applied in high precision grinding and turning machines due to their good dynamic stability and rotational accuracy. However, under the condition of high-speed rotations, the heat generated by the friction of the oil film will cause the shear thinning effect. It not only reduces the rotation accuracy of the spindle but also reduces the service life of the spindle. The surface texture structure and configuration between the planes play the role of homogenizing oil film temperature and preventing the bearing surface wear caused by excessive concentration of temperature, which can change the relative motion from the inside of the oil film and thus improve the performance of the hydrostatic spindle more effectively. In this paper, the influence of the surface texture shape and height on the thrust bearing performance of the hydrostatic spindle is systematically investigated by comparative analysis. The CFD simulations are developed to analyze the computational results based on the theory of viscosity-temperature characteristics. The results show that when the height of the surface structure is 1 ~ 2 times the oil film thickness, the spindle bearing performance is the best. The average temperature in the bearing region is the lowest and the accuracy of the simulations was verified by experimental results. Full article
(This article belongs to the Special Issue High Precision Abrasive Machining: Machines, Processes and Systems)
►▼ Show Figures

Figure 1

18 pages, 5523 KiB  
Article
Using Multivariate Quality Statistic for Maintenance Decision Support in a Bearing Ring Grinder
by Muhammad Ahmer, Fredrik Sandin, Pär Marklund, Martin Gustafsson and Kim Berglund
Machines 2022, 10(9), 794; https://doi.org/10.3390/machines10090794 - 9 Sep 2022
Cited by 1 | Viewed by 2234
Abstract
Grinding processes’ stochastic nature poses a challenge in predicting the quality of the resulting surfaces. Post-production measurements for form, surface roughness, and circumferential waviness are commonly performed due to infeasibility in measuring all quality parameters during the grinding operation. Therefore, it is challenging [...] Read more.
Grinding processes’ stochastic nature poses a challenge in predicting the quality of the resulting surfaces. Post-production measurements for form, surface roughness, and circumferential waviness are commonly performed due to infeasibility in measuring all quality parameters during the grinding operation. Therefore, it is challenging to diagnose the root cause of quality deviations in real-time resulting from variations in the machine’s operating condition. This paper introduces a novel approach to predict the overall quality of the individual parts. The grinder is equipped with sensors to implement condition-based maintenance and is induced with five frequently occurring failure conditions for the experimental test runs. The crucial quality parameters are measured for the produced parts. Fuzzy c-means (FCM) and Hotelling’s T-squared (T2) have been evaluated to generate quality labels from the multi-variate quality data. Benchmarked random forest regression models are trained using fault diagnosis feature set and quality labels. Quality labels from the T2 statistic of quality parameters are preferred over FCM approach for their repeatability. The model, trained from T2 labels achieves more than 94% accuracy when compared to the measured ring disposition. The predicted overall quality using the sensors’ feature set is compared against the threshold to reach a trustworthy maintenance decision. Full article
(This article belongs to the Section Machines Testing and Maintenance)
►▼ Show Figures

Figure 1

21 pages, 10282 KiB  
Article
Design and Performance Evaluation of a Novel Slave System for Endovascular Tele-Surgery
by Chaochao Shi, Shuxiang Guo and Masahiko Kawanishi
Machines 2022, 10(9), 795; https://doi.org/10.3390/machines10090795 - 9 Sep 2022
Cited by 6 | Viewed by 3027
Abstract
Vascular interventional robots have attracted growing attention in recent years. However, current vascular interventional robot systems generally lack force feedback and cannot quickly clamp the catheter/guidewire. The structure of slave systems is unstable and the power transmission is imprecise, increasing the system’s safety [...] Read more.
Vascular interventional robots have attracted growing attention in recent years. However, current vascular interventional robot systems generally lack force feedback and cannot quickly clamp the catheter/guidewire. The structure of slave systems is unstable and the power transmission is imprecise, increasing the system’s safety hazards. Vascular intervention robots generally do not follow traditional surgeons’ operation habits and, thus, it is not easy for them to understand and learn how to operate. Therefore, a novel vascular intervention system is proposed. The slave system can quickly clamp the catheter/guidewire, is compatible with various standard catheter/guidewire sizes, has precise power transmission, and has a stable structure. The surface of the catheter/guidewire is clamped without damage. Whether it is on the master side or the slave side, it follows the habits of traditional operators to a great extent. The results show that the measurement accuracy of the axial force meets the requirements of robot-assisted surgery and the system can track the designed position of the catheter/guidewire in real time. This study makes a certain contribution to the development of master–slave systems for endovascular tele-surgery. Full article
(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)
►▼ Show Figures

Figure 1

20 pages, 4031 KiB  
Article
Development of a Novel Underactuated Robotic Fish with Magnetic Transmission System
by Donato Romano, Akshat Wahi, Marco Miraglia and Cesare Stefanini
Machines 2022, 10(9), 755; https://doi.org/10.3390/machines10090755 - 1 Sep 2022
Cited by 36 | Viewed by 4275
Abstract
In this study, a robotic fish inspired to carangiform swimmers has been developed. The artifact presents a new transmission system that employs the magnetic field interaction of permanent magnets to ensure waterproofness and prevention from any overload for the structure and the actuating [...] Read more.
In this study, a robotic fish inspired to carangiform swimmers has been developed. The artifact presents a new transmission system that employs the magnetic field interaction of permanent magnets to ensure waterproofness and prevention from any overload for the structure and the actuating motor. This mechanism converts the rotary motion of the motor into oscillatory motion. Such an oscillating system, along with the wire-driven mechanism of the tail, generates the required traveling wave in the robotic fish. The complete free swimming robotic fish, measuring 179 mm in length with a mass of only 77 g, was able to maintain correct posture and neutral buoyancy in water. Multiple experiments were conducted to test the robotic fish performance. It could swim with a maximal speed of 0.73 body lengths per second (0.13 m/s) at a tail beat frequency of 3.25 Hz and an electric power consumption of 0.67 W. Furthermore, the robotic fish touched the upper bound of the efficient swimming range, expressed by the dimensionless Strouhal number: 0.43 at 1.75 Hz tail beat frequency. The lowest energy to travel 1 meter was 4.73 Joules for the final prototype. Future works will focus on endowing the robot with energy and navigation autonomy, and on testing its potential for real-world applications such as environmental monitoring and animal–robot interaction. Full article
(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)
►▼ Show Figures

Figure 1

26 pages, 2644 KiB  
Review
Assessment of Industry 4.0 for Modern Manufacturing Ecosystem: A Systematic Survey of Surveys
by Fotios K. Konstantinidis, Nikolaos Myrillas, Spyridon G. Mouroutsos, Dimitrios Koulouriotis and Antonios Gasteratos
Machines 2022, 10(9), 746; https://doi.org/10.3390/machines10090746 - 29 Aug 2022
Cited by 46 | Viewed by 4844
Abstract
The rise of the fourth industrial revolution aspires to digitize any traditional manufacturing process, paving the way for new organisation schemes and management principles that affect business models, the environment, and services across the entire value chain. During the last two decades, the [...] Read more.
The rise of the fourth industrial revolution aspires to digitize any traditional manufacturing process, paving the way for new organisation schemes and management principles that affect business models, the environment, and services across the entire value chain. During the last two decades, the generated advancements have been analysed and discussed from a bunch of technological and business perspectives gleaned from a variety of academic journals. With the aim to identify the digital footprint of Industry 4.0 in the current manufacturing ecosystem, a systematic literature survey of surveys is conducted here, based on survey academic articles that cover the current state-of-the-art. The 59 selected high-impact survey manuscripts are analysed using PRISMA principles and categorized according to their technologies under analysis and impact, providing valuable insights for the research and business community. Specifically, the influence Industry 4.0 exerts on traditional business models, small and medium-sized enterprises, decision-making processes, human–machine interaction, and circularity affairs are investigated and brought out, while research gaps, business opportunities, and their relevance to Industry 5.0 principles are pointed out. Full article
(This article belongs to the Special Issue Design and Manufacturing: An Industry 4.0 Perspective)
►▼ Show Figures

Figure 1

15 pages, 3042 KiB  
Article
Embedded Payload Solutions in UAVs for Medium and Small Package Delivery
by Matteo Saponi, Alberto Borboni, Riccardo Adamini, Rodolfo Faglia and Cinzia Amici
Machines 2022, 10(9), 737; https://doi.org/10.3390/machines10090737 - 27 Aug 2022
Cited by 14 | Viewed by 4517
Abstract
Investigations about the feasibility of delivery systems with unmanned aerial vehicles (UAVs) or drones have been recently expanded, owing to the exponential demand for goods to be delivered in the recent years, which has been further increased by the COVID-19 pandemic. UAV delivery [...] Read more.
Investigations about the feasibility of delivery systems with unmanned aerial vehicles (UAVs) or drones have been recently expanded, owing to the exponential demand for goods to be delivered in the recent years, which has been further increased by the COVID-19 pandemic. UAV delivery can provide new contactless delivery strategies, in addition to applications for medical items, such as blood, medicines, or vaccines. The safe delivery of goods is paramount for such applications, which is facilitated if the payload is embedded in the main drone body. In this paper, we investigate payload solutions for medium and small package delivery (up to 5 kg) with a medium-sized UAV (maximum takeoff of less than 25 kg), focusing on (i) embedded solutions (packaging hosted in the drone fuselage), (ii) compatibility with transportation of medical items, and (iii) user-oriented design (usability and safety). We evaluate the design process for possible payload solutions, from an analysis of the package design (material selection, shape definition, and product industrialization) to package integration with the drone fuselage (possible solutions and comparison of quick-release systems). We present a prototype for an industrialized package, a right prism with an octagonal section made of high-performance double-wall cardboard, and introduce a set of concepts for a quick-release system, which are compared with a set of six functional parameters (mass, realization, accessibility, locking, protection, and resistance). Further analyses are already ongoing, with the aim of integrating monitoring and control capabilities into the package design to assess the condition of the delivered goods during transportation. Full article
(This article belongs to the Special Issue Advances of Machine Design in Italy 2022)
►▼ Show Figures

Figure 1

12 pages, 4588 KiB  
Communication
Baseline for Split DC Link Design in Three-Phase Three-Level Converters Operating with Unity Power Factor Based on Low-Frequency Partial Voltage Oscillations
by Yarden Siton, Vladimir Yuhimenko, Dmitry Baimel and Alon Kuperman
Machines 2022, 10(9), 722; https://doi.org/10.3390/machines10090722 - 24 Aug 2022
Cited by 6 | Viewed by 2100
Abstract
The study sets a baseline for split DC link capacitance values and voltage set points in three-phase three-level AC/DC (or DC/AC) converters operating with unity power factor. In order to equalize the average values of partial DC link voltages, the controller generates a [...] Read more.
The study sets a baseline for split DC link capacitance values and voltage set points in three-phase three-level AC/DC (or DC/AC) converters operating with unity power factor. In order to equalize the average values of partial DC link voltages, the controller generates a zero-sequence containing DC components only while employing neither dedicated DC link capacitance balancing hardware nor high-order zero-sequence component injection. Such a baseline is required in order to evaluate the effectiveness of different DC link capacitance reduction methods proposed in the literature. Unlike most previous works, utilizing neutral point current based on cumbersome analytical expressions to determine neutral point potential oscillations, the instantaneous power balance-based approach is employed in this paper, resulting in greatly simplified and more intuitive expressions. It is demonstrated that while the total DC link voltage is low-frequency ripple-free under unity power factor balanced AC-side operation, split DC link capacitors absorb triple-fundamental frequency power components with one-sixth load power magnitude. This yields significant opposite phase partial voltage ripples. In such a case, selection of DC link capacitances and voltage set points must take into account the expected values of AC-side phase voltage magnitude and split DC link capacitor voltage and current ratings. Simulation and experimental results validate the proposed methodology by application to a 10 kVA T-type converter prototype. Full article
(This article belongs to the Special Issue Advances in High-Power Converters)
►▼ Show Figures

Figure 1

22 pages, 8810 KiB  
Article
Yōkobo: A Robot to Strengthen Links Amongst Users with Non-Verbal Behaviours
by Siméon Capy, Pablo Osorio, Shohei Hagane, Corentin Aznar, Dora Garcin, Enrique Coronado, Dominique Deuff, Ioana Ocnarescu, Isabelle Milleville and Gentiane Venture
Machines 2022, 10(8), 708; https://doi.org/10.3390/machines10080708 - 18 Aug 2022
Cited by 9 | Viewed by 2662
Abstract
Yōkobo is a robject; it was designed using the principle of slow technology and it aims to strengthen the bond between members (e.g., a couple). It greets people at the entrance and mirrors their interactions and the environment around them. It was constructed [...] Read more.
Yōkobo is a robject; it was designed using the principle of slow technology and it aims to strengthen the bond between members (e.g., a couple). It greets people at the entrance and mirrors their interactions and the environment around them. It was constructed by applying the notions of a human–robot–human interaction. Created by joint work between designers and engineers, the form factor (semi-abstract) and the behaviours (nonverbal) were iteratively formed from the early stage of the design process. Integrated into the smart home, Yōkobo uses expressive motion as a communication medium. Yōkobo was tested in our office to evaluate its technical robustness and motion perception ahead of future long-term experiments with the target population. The results show that Yōkobo can sustain long-term interaction and serve as a welcoming partner. Full article
(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)
►▼ Show Figures

Figure 1

18 pages, 8976 KiB  
Article
Design of a Digital Twin for an Industrial Vacuum Process: A Predictive Maintenance Approach
by Mohammad F. Yakhni, Houssem Hosni, Sebastien Cauet, Anas Sakout, Erik Etien, Laurent Rambault, Hassan Assoum and Mohamed El-Gohary
Machines 2022, 10(8), 686; https://doi.org/10.3390/machines10080686 - 12 Aug 2022
Cited by 9 | Viewed by 3433
Abstract
The concept of a digital twin is increasingly appearing in industrial applications, including the field of predictive maintenance. A digital twin is a virtual representation of a physical system containing all data available on site. This paper presents condition monitoring of ventilation systems [...] Read more.
The concept of a digital twin is increasingly appearing in industrial applications, including the field of predictive maintenance. A digital twin is a virtual representation of a physical system containing all data available on site. This paper presents condition monitoring of ventilation systems through the digital twin approach. A literature review regarding the most popular system faults is covered. The motor current signature analysis is used in this research to detect system faults. The physical system is further described. Then, based on the free body diagram concept and Newton’s second law, the equations of motion are obtained. Matlab/Simulink software is used to build the digital twin. The Concordia method and the Fast Fourier Transform analysis are used to process the current signal, and physical and numerical system current measurements are obtained and compared. In the final step of the modeling, specific frequencies were adjusted in the twin to achieve the best simulation. In addition, a statistical approach is used to create a complete diagnostic protocol. Full article
(This article belongs to the Section Machines Testing and Maintenance)
►▼ Show Figures

Figure 1

17 pages, 6208 KiB  
Review
Tracked Locomotion Systems for Ground Mobile Robots: A Review
by Luca Bruzzone, Shahab Edin Nodehi and Pietro Fanghella
Machines 2022, 10(8), 648; https://doi.org/10.3390/machines10080648 - 4 Aug 2022
Cited by 38 | Viewed by 9997
Abstract
The paper discusses the state-of-the-art of locomotion systems for ground mobile robots comprising tracks. Tracked locomotion, due to the large contact surface with the ground, is particularly suitable for tackling soft, yielding, and irregular terrains, but is characterized by lower speed and energy [...] Read more.
The paper discusses the state-of-the-art of locomotion systems for ground mobile robots comprising tracks. Tracked locomotion, due to the large contact surface with the ground, is particularly suitable for tackling soft, yielding, and irregular terrains, but is characterized by lower speed and energy efficiency than wheeled locomotion, and lower obstacle-climbing capability than legged locomotion. Therefore, in recent years academic and industrial researchers have designed a wide variety of hybrid solutions, combining tracks with legs and wheels. The paper proposes three possible parallel taxonomies, based on body architecture, track profile, and track type, to help designers select the most suitable architecture on the basis of the operative necessities. Moreover, modeling, simulation, and design methodologies for tracked ground mobile robots are recalled. Full article
(This article belongs to the Special Issue Feature Review Papers on Automation Systems)
►▼ Show Figures

Figure 1

22 pages, 4464 KiB  
Article
AI-Based Posture Control Algorithm for a 7-DOF Robot Manipulator
by Cheonghwa Lee and Dawn An
Machines 2022, 10(8), 651; https://doi.org/10.3390/machines10080651 - 4 Aug 2022
Cited by 9 | Viewed by 5025
Abstract
With the rapid development of artificial intelligence (AI) technology and an increasing demand for redundant robotic systems, robot control systems are becoming increasingly complex. Although forward kinematics (FK) and inverse kinematics (IK) equations have been used as basic and perfect solutions for robot [...] Read more.
With the rapid development of artificial intelligence (AI) technology and an increasing demand for redundant robotic systems, robot control systems are becoming increasingly complex. Although forward kinematics (FK) and inverse kinematics (IK) equations have been used as basic and perfect solutions for robot posture control, both equations have a significant drawback. When a robotic system is highly nonlinear, it is difficult or impossible to derive both the equations. In this paper, we propose a new method that can replace both the FK and IK equations of a seven-degrees-of-freedom (7-DOF) robot manipulator. This method is based on reinforcement learning (RL) and artificial neural networks (ANN) for supervised learning (SL). RL was used to acquire training datasets consisting of six posture data in Cartesian space and seven motor angle data in joint space. The ANN is used to make the discrete training data continuous, which implies that the trained ANN infers any new data. Qualitative and quantitative evaluations of the proposed method were performed through computer simulation. The results show that the proposed method is sufficient to control the robot manipulator as efficiently as the IK equation. Full article
(This article belongs to the Special Issue Advanced Control Theory with Applications in Intelligent Machines)
►▼ Show Figures

Figure 1

24 pages, 9794 KiB  
Article
CLOVER Robot: A Minimally Actuated Jumping Robotic Platform
by Alejandro Macario-Rojas, Ben Parslew, Andrew Weightman and Katharine Lucy Smith
Machines 2022, 10(8), 640; https://doi.org/10.3390/machines10080640 - 2 Aug 2022
Cited by 4 | Viewed by 2936
Abstract
Robots have been critical instruments to exploration of extreme environments by providing access to environments beyond human limitations. Jumping robot concepts are attractive solutions to negotiate complex and cluttered terrain. However, among the engineering challenges that need to be addressed to enable sustained [...] Read more.
Robots have been critical instruments to exploration of extreme environments by providing access to environments beyond human limitations. Jumping robot concepts are attractive solutions to negotiate complex and cluttered terrain. However, among the engineering challenges that need to be addressed to enable sustained operation of jumping robot concepts in extreme environments, the reduction of mechanical failure modes is one of the most fundamental. This study sets out to develop a jumping robot design, with a focus on a minimal actuation to support reduced mechanism maintenance and thus limit the number of mechanical failure modes. We present the synthesis of a Sarrus-style linkage to constrain the system to a single translational degree of freedom thus removing the need for synchronising gears, which exhibit high failure rates in dusty environments. We have restricted the present research to vertical solid jumps to assess the performance of the fundamental main-drive linkage. A laboratory demonstrator assists the transfer of theoretical concepts and approaches to practical implementation. The laboratory demonstrator performs jumps with 63% potential-to-kinetic energy conversion efficiency, with a theoretical maximum of 73%. Satisfactory operation opens up design optimisation and directional jump capability towards the development of a jumping robotic platform for extreme environments exploration. Full article
(This article belongs to the Special Issue Advances in Applied Mechatronics)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying article 201-250 on page 5 of 9.

Go to page    first_page chevron_left 3 4 5 6 7 chevron_right last_page
Back to TopTop