Vibration, Volume 7, Issue 4 (December 2024) – 13 articles

This study presents a comprehensive investigation of an innovative mechanical system inspired by recent advancements in metamaterials; more specifically, the work is focused on origami-type structures due to their intriguing mechanical properties. Originating from specific fields such as aerospace for their lightweight and foldable characteristics, origami mechanical devices exhibit unique nonlinear stiffness; in particular, when suitably designed, they show Quasi-Zero Stiffness (QZS) characteristics within a specific working range. The QZS property, aligned with the High Static Low Dynamic (HSLD) stiffness concept, suggests promising applications such as a low-frequency mechanical passive vibration isolator. The study explores the vibration isolation characteristics of origami-type suspensions, with a particular emphasis on their potential application as low-frequency passive vibration isolators. The Kresling Origami Module (KOM) has been selected for its compactness and compatibility with 3D printers. A detailed analysis using 3D CAD, Finite Element Analysis, and experimental testing has been carried out. The investigation includes the analysis of the influence of geometric parameters on the nonlinear force–displacement curve. Multibody simulations validate the low-frequency isolation properties within the QZS region, as well as disparities in dynamic properties beyond the QZS range. The study underscores the transformative potential of origami-type metamaterials in enhancing low-frequency vibration isolation technology. It also highlights challenges related to material properties and loading mass variations, providing valuable insights for future developments in this promising field. Full article

This paper presents an experimental method for testing composite insulators based on vibration testing. The method used investigated the propagation, signal shape, and distortion of excited mechanical waves under the influence of defects. The aim of the method was to identify defects in the core of a composite insulator that cannot be economically detected by currently available diagnostic methods in field conditions. Therefore, this experiment aimed to distinguish between the mechanical waves’ characteristics of damaged and intact insulators using inexpensive tools. This article seeks to provide a basis for mechanical vibration diagnostics of composite insulators by demonstrating that damage to the core can result in a perceptible difference in the characteristics of mechanical waves when testing within the frequency range of audible sound. Full article

This paper presents a comprehensive analysis of the influence of rotary table velocity, weight-on-bit, and viscous damping on the drill string stick–slip vibration. The analysis allows for studying the qualitative and quantitative variation of the dynamic response of the drill pipes and drill collars/bit. To achieve this goal, a robust and practical finite element (FE) model of the full-scaled drill string was developed based on a velocity-weakening formulation of the nonlinear bit–rock interaction. A detailed investigation of damping parameters was carried out. The performance of the developed model was verified through comparisons with a lumped-parameter model and a field test example. Parametric studies on the stick–slip response of the entire drill string under different field operational conditions were conducted. The dynamical time series of the system response were analyzed in terms of the phase planes, response spectra, and descriptive statistics of the drill pipes and drill collars. The findings of the study revealed that for a realistic drill string geometry, the angular velocity (i.e., mean, peak-to-peak amplitude, and standard deviation) and dominant frequency of self-excited torsional stick–slip oscillations along the drill pipes and drill collars/bit are mainly governed by the rotary table velocity. Furthermore, it was shown that the contribution of higher harmonics in the torsional stick–slip response of the drill pipes is more substantial than the drill collars/bit. Full article

This paper presents an advanced modular modeling approach for vertical vibration analysis of dynamic systems using the Generalized Receptance Coupling and Frequency-Based Substructuring (GRCFBS) method. The focus is on a four-DoF half-vehicle model comprising three key subsystems: front suspension, rear suspension, and the vehicle’s trimmed body. The proposed technique is designed to predict dynamic responses in reconfigurable systems across various applications, including automotive, robotics, mechanical machinery, and aerospace structures. By coupling the receptance matrices (FRFs) of individual vehicle modules, the overall system receptance matrix is efficiently derived in a disassembled configuration. Two generalized coupling methods, originally developed by Jetmundsen and D.D. Klerk, are employed to determine the complete vehicle’s receptance matrix from its subsystems. Validation is achieved by comparing the results with established methods, such as direct solution and modal analysis, demonstrating high accuracy and reliability for complex dynamic systems. This modular approach allows for the creation of reduced-order models focused on key measurement points without the need for detailed system representation. The method offers significant advantages in early-stage vehicle development, providing critical insights into system vibration behavior. Full article

Many industrial processes, from manufacturing to food processing, incorporate rotating elements as principal components in their production chain. Failure of these components often leads to costly downtime and potential safety risks, further emphasizing the importance of monitoring their health state. Vibration signal analysis is now a common approach for this purpose, as it provides useful information related to the dynamic behavior of machines. This research aimed to conduct a comprehensive examination of the current methodologies employed in the stages of vibration signal analysis, which encompass preprocessing, processing, and post-processing phases, ultimately leading to the application of Artificial Intelligence-based diagnostics and prognostics. An extensive search was conducted in various databases, including ScienceDirect, IEEE, MDPI, Springer, and Google Scholar, from 2020 to early 2024 following the PRISMA guidelines. Articles that aligned with at least one of the targeted topics cited above and provided unique methods and explicit results qualified for retention, while those that were redundant or did not meet the established inclusion criteria were excluded. Subsequently, 270 articles were selected from an initial pool of 338. The review results highlighted several deficiencies in the preprocessing step and the experimental validation, with implementation rates of 15.41% and 10.15%, respectively, in the selected prototype studies. Examination of the processing phase revealed that time scale decomposition methods have become essential for accurate analysis of vibration signals, as they facilitate the extraction of complex information that remains obscured in the original, undecomposed signals. Combining such methods with time–frequency analysis methods was shown to be an ideal combination for information extraction. In the context of fault detection, support vector machines (SVMs), convolutional neural networks (CNNs), Long Short-Term Memory (LSTM) networks, k-nearest neighbors (KNN), and random forests have been identified as the five most frequently employed algorithms. Meanwhile, transformer-based models are emerging as a promising venue for the prediction of RUL values, along with data transformation. Given the conclusions drawn, future researchers are urged to investigate the interpretability and integration of the diagnosis and prognosis models developed with the aim of applying them in real-time industrial contexts. Furthermore, there is a need for experimental studies to disclose the preprocessing details for datasets and the operational conditions of the machinery, thereby improving the data reproducibility. Another area that warrants further investigation is differentiation of the various types of fault information present in vibration signals obtained from bearings, as the defect information from the overall system is embedded within these signals. Full article

Vibrations generated from equipment mounted on ships radiate into the water and affect covert operation capabilities. Accordingly, various studies are being conducted to reduce vibration transmitted from mounted equipment. In this study, a system consisting of mounting equipment, a 3-axis active mount, a middle pedestal, and a lower mount of the middle pedestal was modeled using a finite element analysis program, and a mobility model was constructed by calculating the frequency response function between the positions required for analysis. The error signal (primary path) obtained using the mobility model and the response at the operating point by the control force of the actuator (secondary path) are applied to the narrowband Fx-LMS algorithm for vibration control, and the control performance was compared. Through coupling analysis of the middle pedestal, the control influence according to the rigidity of the middle pedestal was analyzed. As a result of the control simulation, the time required for vibration control was controlled approximately 6 times faster in the model, with increased stiffness of the middle pedestal, and the vibration reduction performance was predicted to improve by a minimum of 0.9 dB and a maximum of 13.3 dB. Through this study, a simulation model that can provide a guide for the design of the middle pedestal of a ship was obtained, and it is expected that it can be utilized for a preliminary design review before manufacturing the middle pedestal of a ship. Full article

This work investigates the conditions for net flow generation by a straight tube with a cross-sectional area harmonically varying in time that connects two tanks—a problem that is mainly found in the design of impedance pumps. By assuming a quasi-one-dimensional flow and applying continuity and momentum equations, a first-order differential equation with respect to the flow rate is derived and presented for the first time, including a nonlinear term that is responsible for net flow rate generation. Namely, the net flow rate is found to be nonzero (as is the nonlinear term) if the cross-sectional areas of the two tanks are unequal and one of them is smaller than that of the straight tube. In this case, the flow is directed from the smaller to the larger tank and the net flow rate increases with the frequency of the tube’s cross-sectional area variation. In contrast, when the tanks’ cross-sections are equal, the net flow is generated only if a valve is installed, e.g., at one end of the tube, due to the large asymmetries imposed in the hydraulic losses with respect to the tube mid-length. Compared with constant valve opening, the net flow rate is augmented significantly if the valve opening is time-dependent. By employing the same equation, the flow rate of an intra-aortic counter-pulsating balloon pump is also examined, in which the valve (representing the aortic valve) opens during the shrinkage of the tube, and it is shown that the net flow rate increases with the frequency and amplitude of the tube’s cross-sectional area. Conclusively, the harmonic oscillation in time of a tube’s wall can cause unidirectional flow only if asymmetric losses are present with respect to its mid-length. Full article

In engineering applications, the accuracy of on-load tap changer (OLTC) mechanical fault identification methods based on vibration signals is constrained by the quantity and quality of the samples. Therefore, a novel small-sample-size OLTC mechanical fault identification method incorporating short-time Fourier transform (STFT), synchrosqueezed wavelet transform (SWT), a dual-stream convolutional neural network (DSCNN), and support vector machine (SVM) is proposed. Firstly, the one-dimensional time-series vibration signals are transformed using STFT and SWT to obtain time–frequency graphs. STFT time–frequency graphs capture the global features of the OLTC vibration signals, while SWT time–frequency graphs capture the local features of the OLTC vibration signals. Secondly, these time–frequency graphs are input into the CNN to extract key features. In the fusion layer, the feature vectors from the STFT and SWT graphs are combined to form a fusion vector that encompasses both global and local time–frequency features. Finally, the softmax classifier of the traditional CNN is replaced with an SVM classifier, and the fusion vector is input into this classifier. Compared to the traditional fault identification methods, the proposed method demonstrates higher identification accuracy and stronger generalization ability under the conditions of small sample sizes and noise interference. Full article

This paper presents a methodology for accurately incorporating the nonlinearity of boundary conditions (BCs) into the mode shapes, natural frequencies, and dynamic behaviour of analytical beam models. Such models have received renewed interest in recent years as a result of their successful implementation in state-of-the-art multiphysics problems. To address the need for this boundary nonlinearity to be more completely captured in the equations of motion, a nonlinear algebra expansion of the classical linear approach for developing solvability conditions for natural frequencies and mode shapes is presented. The method is applicable to any BC that can be accurately represented in polynomial form, either explicitly or through the application of a Taylor expansion; this is the only assumption made in removing the need for the use of analytical approximations of the dynamics themselves. By reducing the BCs of the beam to a system of polynomials, it is possible to utilise the tensor resultant to develop these solvability conditions analogous to the conditions placed on the matrix determinant in linear, classical cases. The approach is first derived for a general set of nonlinear BCs before being applied to two example systems to investigate the importance of including nonlinear tip behaviour in the BCs to accurately predict the system response. In the first, a theoretical, symmetric system, in which a beam is supported by nonlinear springs, is used to explore both the applicability of the methodology and the improvements it can make to the accuracy of the model. Then, the more practical example of a cantilever beam with repulsive magnetic interaction at the tip is used to more explicitly assess the importance of properly incorporating boundary nonlinearity into multiphysics problems. Full article

Track and preventive maintenance are necessary for the safe and comfortable operation of railways. Track displacement measured by track inspection vehicles or trolleys has been primarily used for track management. Thus, vibration data measured in in-service vehicles have not been extensively used for track management. In this study, we propose a new technique for estimating track irregularities from measured car body vibration for track management. The correlation between track irregularity and car body vibration was analysed using a multibody dynamics simulation of travelling rail vehicles. Gaussian process regression (GPR) was applied to the track irregularity and car body vibration data obtained from the simulation, and a method was proposed to estimate the track irregularities from the constructed regression model. The longitudinal-level, alignment, and cross-level irregularities were estimated from the measured car body vibrations and travelling speeds on a regional railway, and the results were compared with the actual track irregularity data. The results showed that the proposed method is applicable for track irregularity management in regional railways. Full article

CERN, the European Organisation for Nuclear Research is studying the feasibility of the Future Circular Collider, considering both financial and technical aspects. One of the challenges is that the performance of particle accelerators relies on the dynamic stability of structures, affected by multiple sources of vibrations, including crosstalk vibration between two particle accelerators, the Booster and Collider, in the Future Circular Lepton Collider. This research aims to find a methodology for determining transfer functions, specifically crosstalk transfer functions, between the Collider and Booster within an underground tunnel. Also, it aims to determine how significant crosstalk is compared to the vibration from other sources, such as ground vibrations. The transfer functions of the tunnel were independently determined from internal structures using the Finite Element Method, employing 2D plane strain and the standard absorbing boundary to model the underground tunnel. It was found that the overall gain of crosstalk was less than 10% of that of ground-to-magnetic axis of either the Collider or Booster. This method may be used to optimize the tunnel layout from a vibration point of view. It appears that vibrations from crosstalk are far lower compared to vibrations from ground vibrations. Full article

Shock-induced vibrations transmitted from the racket to the tennis player’s upper limb have interested researchers, whether for investigating their effect on injury risk, or for designing new equipment. Measuring these vibrations is, however, very challenging in an ecological playing situation: sensors must be of very high quality in order to precisely measure high-energy and broad-frequency signals, as well as non-invasive in order to allow the players to perform their usual movements. The working hypothesis of this paper is that contactless sound recordings of the ball/racket impact carry the same information as direct vibratory measurements. The present study focuses on the tennis serve, as being tennis’ most energy-demanding stroke, therefore possibly being the most traumatic stroke for the upper limb. This article aims (a) to evaluate the propagation of vibration from the racket to the upper limb; and (b) to identify correlations with acoustic signals collected simultaneously. Eight expert tennis players performed serves with three rackets and two ball spin effects. Accelerometers measured the vibration on the racket and at five locations on the upper limb, and a microphone measured the impact sound. Resulting signals were analyzed in terms of energy and spectral descriptors. Results showed that flat serves produced louder sounds, higher vibration levels, lower acoustic spectral centroids, and higher vibratory spectral centroids than kick serves. The racket only had a marginal influence. Similarities between acoustic and vibratory measurements were found (levels were correlated), but so were differences (spectral centroids tended to be negatively correlated), encouraging further studies on the link between sound and vibration for the in situ measurement of shock-induced vibration. Full article

In today’s interconnected industrial landscape, the ability to predict and monitor the operational status of equipment is crucial for maintaining efficiency and safety. Diesel engines, which are integral to numerous industrial applications, require reliable fault detection mechanisms to reduce operational costs, prevent unplanned downtime, and extend equipment lifespan. Traditional anomaly detection methods, such as thermometry, wear indicators, and radiography, often necessitate significant expertise, involve costly equipment shutdowns, and are limited by high usage costs and accessibility. Addressing these challenges, this study introduces a novel approach for fault detection in diesel engines by analyzing torsional vibration data in the time domain. The proposed method leverages short-term Fourier transform (STFT) and continuous wavelet transform (CWT) techniques, integrated with a convolutional neural network (CNN) to identify hidden patterns and diagnose engine conditions accurately. The method achieved a detection accuracy of 96.5% with STFT and 92.2% with CWT. To ensure robustness, the model was tested under various noise conditions, maintaining accuracies above 70% for noise levels up to 40%. This research provides a practical and efficient solution for real-time fault detection in diesel engines, offering a significant improvement over traditional methods in terms of cost, accessibility, and ease of implementation. Full article