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30 pages, 6496 KiB

Open AccessArticle

Enhancement Method Based on Multi-Strategy Improved Pelican Optimization Algorithm and Application to Low-Illumination Forest Canopy Images

by Xiaohan Zhao, Liangkuan Zhu, Jingyu Wang and Alaa M. E. Mohamed

Forests 2024, 15(10), 1783; https://doi.org/10.3390/f15101783 - 11 Oct 2024

Viewed by 788

Abstract

Enhancement is a crucial step in the field of image processing, as it significantly improves image analysis and understanding. One of the most commonly used methods for image contrast enhancement is the incomplete beta function (IBF). However, the key challenge lies in determining [...] Read more.

Enhancement is a crucial step in the field of image processing, as it significantly improves image analysis and understanding. One of the most commonly used methods for image contrast enhancement is the incomplete beta function (IBF). However, the key challenge lies in determining the optimal parameters for the IBF. This paper introduces a multi-strategy improved pelican optimization algorithm (MIPOA) to address the low-illumination color image enhancement problem. The MIPOA algorithm utilizes a nonlinear decreasing coefficient to boost the exploration ability and convergence speed, whereas the Hardy–Weinberg principle compensates for the unsound exploitation mechanism. Additionally, the diversity variation operation improves the ability of the algorithm to escape local optimal solutions. The performance of the proposed MIPOA algorithm was evaluated using a benchmark function and was found to outperform five variant algorithms in extensive comparisons. To further harness the potential of the MIPOA algorithm, the authors propose a low-light forest canopy image enhancement method based on the MIPOA algorithm. The MIPOA algorithm searches for the optimal parameters of the IBF, leading to fast contrast enhancement of the image. The segmented gamma correction function is designed to enhance the brightness of the low-light forest canopy images. In determining the optimal parameters of IBF, the MIPOA algorithm demonstrates superior performance compared to other intelligent algorithms in the feature similarity index (FSIM), entropy, and contrast improvement index (CII) of 75%, 58.33%, and 75%, respectively. The proposed MIPOA-based enhancement method achieves a moderate pixel mean and surpasses the conventional enhancement method with an average gradient of 91.67%. The experimental results indicate that the MIPOA effectively addresses the limitations of low optimization accuracy in IBF parameters, and the enhancement method based on the MIPOA provides a more efficacious approach for enhancing low-light forest canopy images. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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26 pages, 12307 KiB

Open AccessArticle

Research on the Performance and Control Strategy of Electro-Hydraulic Servo System for Selective Hole Digging Tree Planter

by Binhai Zhu, Jiuqing Liu, Hang Yu, Li Yu, Zhenli Wang, Huan Zhou and Chunmei Yang

Forests 2024, 15(10), 1744; https://doi.org/10.3390/f15101744 - 2 Oct 2024

Viewed by 667

Abstract

Compared to agricultural environments, afforestation sites are more complex, often presenting issues such as undulating and uneven terrain. These conditions lead to instability in hole digging depth and plant spacing during continuous movement, and the hole shape may not meet expectations. Additionally, the [...] Read more.

Compared to agricultural environments, afforestation sites are more complex, often presenting issues such as undulating and uneven terrain. These conditions lead to instability in hole digging depth and plant spacing during continuous movement, and the hole shape may not meet expectations. Additionally, the hydraulic system exhibits slow response speed and long steady-state time, affecting the quality of sapling planting. To address these issues, this paper designs an intelligent planting control system for intermittent hole digging under continuous dynamic movement, based on a large tree planter. The focus is on studying the dynamic accuracy of the hole digging cylinder to resolve the instability of plant spacing and planting depth in actual planting processes. Firstly, a motion trajectory model of the intermittent hole digging mechanism is established to obtain the relationship between the displacement trajectory of the rotating cutter and the displacements of the floating cylinder and the hole digging cylinder. Secondly, a mathematical model of the electro-hydraulic servo system is established to control the dynamic accuracy of the hole digging operation. Finally, a Simulink simulation model of the system is established to analyze the performance indicators of the hydraulic system during operation using step and sinusoidal excitation signals. The test results show that the displacement of the hydraulic piston rod can ensure a linear extension trend within the range of 0 to 0.4 m, and the extension distance of the hole digging cylinder in the planting system is 0 to 0.35 m, ensuring linear change within this stroke. When the system’s extension command is 1 V, the actual output is 0.6 m, with a relative error of less than 10% compared to the simulation value, indicating that the control strategy can effectively improve the dynamic performance of the system. When the hydraulic system is in a steady-state extension state at 50 to 58.6 s, the relative error with the simulation value is 7.3%, meeting the “double ten indicators” requirement. The research results clearly verify the superior performance of the proposed intelligent control system, and the proposed control strategy has great potential in practical applications, promising to improve afforestation quality by stabilizing planting spacing and planting depth. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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21 pages, 6985 KiB

Open AccessArticle

An Improved YOLOv5 Algorithm for Bamboo Strip Defect Detection Based on the Ghost Module

by Ru-Xiao Yang, Yan-Ru Lee, Fu-Shin Lee, Zhenying Liang and Yang Liu

Forests 2024, 15(9), 1480; https://doi.org/10.3390/f15091480 - 23 Aug 2024

Viewed by 634

Abstract

Detecting surface defects in bamboo strips is essential for producing Asian bamboo products. Currently, the detection of surface defects in bamboo strips mainly relies on manual labor. The labor intensity is high, and the detection efficiency is low. Improving the speed and accuracy [...] Read more.

Detecting surface defects in bamboo strips is essential for producing Asian bamboo products. Currently, the detection of surface defects in bamboo strips mainly relies on manual labor. The labor intensity is high, and the detection efficiency is low. Improving the speed and accuracy of identifying bamboo strip defects is crucial in enhancing enterprises’ production efficiency. Hence, this research designs a lightweight YOLOv5s neural network algorithm using the Ghost module to identify surface defects of bamboo strips. The research introduces an attention mechanism CA module to improve the recognition ability of the model target; the research also implements a C2f model to enhance the network performance and the surface quality of bamboo strips. The experimental results show that after training with the acquired image dataset, the YOLOv5s model can exert an intelligent detection effect on five common types of defects in bamboo strips, and the Ghost module makes YOLOv5s lightweight, which can effectively reduce model parameters and improve detection speed while maintaining recognition accuracy. Meanwhile, the C2f module and CA module can further leverage the model’s ability to identify specific defects in bamboo strips after lightweight improvement. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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12 pages, 2111 KiB

Open AccessArticle

Cut-to-Length Harvesting Prediction Tool: Machine Learning Model Based on Harvest and Weather Features

by Rodrigo Oliveira Almeida, Richardson Barbosa Gomes da Silva and Danilo Simões

Forests 2024, 15(8), 1398; https://doi.org/10.3390/f15081398 - 10 Aug 2024

Viewed by 734

Abstract

Weather is a significant factor influencing forest health, productivity, and the carbon cycle. However, our understanding of these effects is limited for many regions and ecosystems. Assessing the impact of weather variability on harvester productivity from plantation forests may assist in forest planning [...] Read more.

Weather is a significant factor influencing forest health, productivity, and the carbon cycle. However, our understanding of these effects is limited for many regions and ecosystems. Assessing the impact of weather variability on harvester productivity from plantation forests may assist in forest planning through the use of data modeling. We investigated whether weather data combined with timber harvesting attributes could be used to create a high-performance model that could accurately predict harvester productivity in Eucalyptus plantations using machine learning. Furthermore, we aimed to provide an online application to assist forest managers in applying the model. For the modeling, we considered 15 weather and timber harvesting attributes. We considered productivity as the target attribute. We subjected the database to 24 common algorithms in default mode and compared them according to error metrics and accuracy. From the timber harvesting features combined with weather features, the Catboost model can predict the productivity of harvesters in a tuned mode, with a coefficient of determination of 0.70. The use of weather data combined with timber harvesting attributes in the model is an accurate approach for predicting harvester productivity in Eucalyptus plantations, allowing for the creation of an online, free application to assist forest managers. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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27 pages, 8802 KiB

Open AccessArticle

Automated Shape Correction for Wood Composites in Continuous Pressing

by Yunlei Lv, Yaqiu Liu, Xiang Li, Lina Lu and Adil Malik

Forests 2024, 15(7), 1118; https://doi.org/10.3390/f15071118 - 27 Jun 2024

Viewed by 734

Abstract

The effective and comprehensive utilization of forest resources has become the theme of the global “dual-carbon strategy”. Forestry restructured wood is a kind of wood-based panel made of wood-based fiber composite material by high-temperature and high-pressure restructuring–molding, and has become an important material [...] Read more.

The effective and comprehensive utilization of forest resources has become the theme of the global “dual-carbon strategy”. Forestry restructured wood is a kind of wood-based panel made of wood-based fiber composite material by high-temperature and high-pressure restructuring–molding, and has become an important material in the field of construction, furniture manufacturing, as well as derivative processing for its excellent physical and mechanical properties, decorative properties, and processing performance. Taking Medium Density Fiberboard (MDF) as the recombinant material as the research object, an event-triggered synergetic control mechanism based on interventional three-way decision making is proposed for the viscoelastic multi-field coupling-distributed agile control of the “fixed thickness section” in the MDF continuous flat-pressing process, where some typical quality control problems of complex plate shape deviations including thickness, slope, depression, and bump tend to occur. Firstly, the idea of constructing the industrial event information of continuous hot pressing based on information granulation is proposed, and the information granulation model of the viscoelastic plate shape process mechanism is established by combining the multi-field coupling effect. Secondly, an FMEA-based cyber granular method for diagnosing and controlling the plate thickness diagnosis and control failure information expression of continuous flat pressing is proposed for the problems of plate thickness control failure and plate thickness deviation defect elimination that are prone to occur in the continuous flat-pressing process. The precise control of the plate thickness in the production process is realized based on event-triggered control to achieve the intelligent identification and processing of the various types of faults. The application test is conducted in the international mainstream production line of a certain type of continuous hot-pressing equipment for the production of 18 mm plate thickness; the synergistic effect is basically synchronized after 3 s, the control accuracy reaches 30%, and the average value of the internal bond strength is 1.40, which ensures the integrity of the slab. Practical tests show that the method in the actual production is feasible and effective, with detection and control accuracy of up to ±0.05 mm, indicating that in the production of E0- and E1-level products, the rate of superior products can reach more than 95%. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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17 pages, 32075 KiB

Open AccessArticle

Enhancing Afforestation Practices in Hilly Terrain: A Study on Soil Disturbance by Earth Augers Based on the Discrete Element Method

by Guofu Wang, Wei Zhang, Xingliang Diao, Min Ji, Hu Miao and Meiling Chen

Forests 2024, 15(1), 190; https://doi.org/10.3390/f15010190 - 17 Jan 2024

Cited by 2 | Viewed by 1368

Abstract

Afforestation operations in hilly regions are both arduous and unsafe. The mechanized afforestation method that takes into account soil and water conservation measures is deemed highly important. This paper examines the operational process and the auger’s mechanism of digging below the ground using [...] Read more.

Afforestation operations in hilly regions are both arduous and unsafe. The mechanized afforestation method that takes into account soil and water conservation measures is deemed highly important. This paper examines the operational process and the auger’s mechanism of digging below the ground using the discrete element method (DEM). Using this model, soil disturbance parameters and reaction forces are satisfactorily predicted, exhibiting similar trends to experimental observations. This research also examines the influence of key parameters on soil disturbance and distribution patterns and analyzes the conditions and mechanisms of the formation of fish-scale pits to preserve soil and water. A field experiment of pit digging in woodland is carried out to test the performance of the device. The error rates for the actual and simulated values of the efficiency of conveying soil and the distance of throwing soil on plain terrain and slopes were 12.7% and 8.2%, and 8.6% and 15.7%, respectively. Overall, this research provides a theoretical basis for the innovative exploration, development, and optimized design of earth augers in hilly regions. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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21 pages, 6896 KiB

Open AccessArticle

Sliding Cutting and Cutting Parameters of Concentric Curvilineal Edge Sliding Cutter for Caragana korshinskii (C.K.) Branches

by Haifeng Luo, Shaojun Guo, Zhenkun Zhi and Jiangming Kan

Forests 2023, 14(12), 2379; https://doi.org/10.3390/f14122379 - 5 Dec 2023

Cited by 4 | Viewed by 1211

Abstract

To realize the reduction in cutting force and guarantee pruning section quality in the pruning and stubble work of Caragana korshinskii (C.K.), a concentric curvilineal edge sliding cutter was proposed and the related cutting characteristics were studied. The impacts of branch diameter (D), [...] Read more.

To realize the reduction in cutting force and guarantee pruning section quality in the pruning and stubble work of Caragana korshinskii (C.K.), a concentric curvilineal edge sliding cutter was proposed and the related cutting characteristics were studied. The impacts of branch diameter (D), cutting speed (

V_{c}

), blade wedge angle (

β

), cutting clearance (

c

) and moisture content (W) on peak torque (T) and cutting energy (E) with this cutter were explored in single-factor tests. On the basis of the Box—Behnken principle, a multi-factor test was further conducted based on the single-factor tests with

V_{c}

,

β

and c as influencing factors and with T and E as targets, and a regression model was established. Test results indicate that the peak torque (T) increases with the increase in D and

β

and reduces with the growth of

V_{c}

and W; with the increase in

c

, it reduces first and then rises; the cutting energy (E) increases with the growth of D and

β

, declines with the increase in W and diminishes first and then rises with the increase in

V_{c}

and

c

. The optimal parameter combination of the regression model was obtained with

V_{c}

of 2.16 rad/s,

β

of 20

°

and

c

of 1.0 mm, which resulted in a T of 17.25 N·m and P of 7.03 J. The discrepancies between the observed and forecasted values for T and E are 0.87% and 5.004%. New cutting tool and data support for the development of subsequent C.K. branch stubble equipment can be obtained with this new sliding cutter. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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22 pages, 5143 KiB

Open AccessArticle

A Deformable Shape Model for Automatic and Real-Time Dendrometry

by Lucas A. Wells and Woodam Chung

Forests 2023, 14(12), 2299; https://doi.org/10.3390/f14122299 - 23 Nov 2023

Viewed by 1180

Abstract

We present a stereo image-based algorithm for tree stem diameter measurement and form analysis. The algorithm uses planar parametric curves to represent two-dimensional projections of tree stems in stereo images. The curves evolve according to an energy formulation based on the gradients of [...] Read more.

We present a stereo image-based algorithm for tree stem diameter measurement and form analysis. The algorithm uses planar parametric curves to represent two-dimensional projections of tree stems in stereo images. The curves evolve according to an energy formulation based on the gradients of the images and inductive priors related to biomechanics and morphology of tree stems. After energy minimization, the curves are reconstructed to three dimensions, allowing for diameter measurements at any point along the height of the stem. We describe the algorithm and report the validation test results comparing predicted diameter measurements to external observations. Our findings demonstrate that the algorithm can automatically estimate diameters for trees within 20 m of the camera with an error of 5.52%. We highlight how this method can aid product value optimization through taper analysis and sweep or crook detection. A run-time analysis shows that the algorithm can estimate dendrometric variables for ten trees simultaneously at 15 frames per second on a consumer-grade computer. Furthermore, we discuss the opportunity to produce training data for machine learning algorithms that generalize across domains and eliminate the need to manually tune parameters. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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13 pages, 6661 KiB

Open AccessArticle

Remote Monitoring of Amur Tigers in Forest Ecosystems Using Improved YOLOX Algorithm

by Yonghua Xie and Wenhua Yu

Forests 2023, 14(10), 2000; https://doi.org/10.3390/f14102000 - 5 Oct 2023

Cited by 3 | Viewed by 1211

Abstract

In response to the challenge of collecting behavioral data on Amur tigers living in forests, a remote real-time data collection approach is proposed. In this article, a novel attention mechanism named CBAM-E is introduced, and CBAM-E as well as the CIoU loss function [...] Read more.

In response to the challenge of collecting behavioral data on Amur tigers living in forests, a remote real-time data collection approach is proposed. In this article, a novel attention mechanism named CBAM-E is introduced, and CBAM-E as well as the CIoU loss function are incorporated into the YOLOX object detection algorithm, resulting in a new YOLOX model. The new model demonstrates significant performance improvements over the original model, with the

{m A P}_{0.5}

detection accuracy metric rising from 97.32 to 98.18%, indicating a boost of 0.86%, and the

{m A P}_{0.75}

metric increasing from 75.10 to 78.70%, marking an enhancement of 3.60%. The enhanced algorithm is subsequently applied to remote terminal information collection, offering a reference for detection algorithms in the study of wild behaviors of Amur tigers in forests, biodiversity conservation, and the collection of related field data about Amur tigers in the wild. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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10 pages, 7358 KiB

Open AccessArticle

Study on the Milling Machinability of Bamboo-Based Fiber Composites

by Yucheng Ding, Tongbin Liu, Yaqiang Ma, Chunmei Yang, Changyu Shi, Yongjian Cao and Jiawei Zhang

Forests 2023, 14(9), 1924; https://doi.org/10.3390/f14091924 - 21 Sep 2023

Cited by 2 | Viewed by 1470

Abstract

Bamboo-based fiber composites, known as recombinant bamboo, have emerged as a new material in the construction and decoration industry. With its excellent mechanical and ornamental properties, recombinant bamboo is gaining popularity. However, its high hardness and abrasion resistance pose challenges in the milling [...] Read more.

Bamboo-based fiber composites, known as recombinant bamboo, have emerged as a new material in the construction and decoration industry. With its excellent mechanical and ornamental properties, recombinant bamboo is gaining popularity. However, its high hardness and abrasion resistance pose challenges in the milling process. To address this, we conducted an experimental study to investigate the milling machinability of recombinant bamboo. We studied the impact of various factors—fiber angle, feed rate, and spindle speed—on the tangential and normal roughness of milled surfaces. Our findings indicated that increasing the spindle speed within an acceptable range can effectively mitigate issues such as carbonization and endface cracking on a milled surface. Additionally, we developed a prediction model to assess the probability of end splitting in recombinant bamboo. This research aimed to enhance the milling quality of recombinant bamboo, improve control over surface roughness, reduce the likelihood of end splitting, and, ultimately, expand application possibilities. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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17 pages, 14110 KiB

Open AccessArticle

Experimental Study on the Dynamic Stability of Circular Saw Blades during the Processing of Bamboo-Based Fiber Composite Panels

by Yucheng Ding, Yaqiang Ma, Tongbin Liu, Jiawei Zhang and Chunmei Yang

Forests 2023, 14(9), 1855; https://doi.org/10.3390/f14091855 - 12 Sep 2023

Cited by 5 | Viewed by 1177

Abstract

Bamboo-based fiber composite panel is a new type of composite material with excellent performance. When processing bamboo-based fiber composite panels, the dynamic stability of the circular saw blade affects the surface quality of the product and the life of the machinery and equipment. [...] Read more.

Bamboo-based fiber composite panel is a new type of composite material with excellent performance. When processing bamboo-based fiber composite panels, the dynamic stability of the circular saw blade affects the surface quality of the product and the life of the machinery and equipment. Sawing heat and vibration characteristics can significantly affect the dynamic stability of circular saw blades. Circular saw blade temperature and vibration characteristics are affected by the processing parameters, and the circular saw blade temperature and vibration characteristics are analyzed by changing the processing parameters. Adopting the thermoset coupling model can be used to analyze the change rule of circular saw blade temperature when sawing bamboo-based fiber composite boards, and at the same time to analyze the change rule of circular saw blade temperature, vibration speed, and vibration acceleration through the use of by CCD experiments. The regression equations for circular saw blade temperature, vibration velocity, and vibration acceleration were derived through the use of ANOVA and significance analysis. The thermoset coupling model predictions agree with the experimental results, and the density of the isotherms is progressively thinner as the temperature is conducted from the serrated region to the body of the saw. Finally, the accuracy of the regression equations for circular saw blade temperature, vibration velocity, and vibration acceleration was checked via error analysis. The temperature change regression equation has the highest fitting accuracy, with an average error of only 1.37%; the vibration velocity and vibration acceleration regression equations have poorer fitting accuracy, with an average error of 9.5% and 11.45%, respectively, but all of them have sufficient accuracy to predict the dynamic stability of circular saw blades. The results of the study can provide some guidance for the innovative design of circular saw blades. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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16 pages, 8507 KiB

Open AccessArticle

Detection of Forestry Pests Based on Improved YOLOv5 and Transfer Learning

by Dayang Liu, Feng Lv, Jingtao Guo, Huiting Zhang and Liangkuan Zhu

Forests 2023, 14(7), 1484; https://doi.org/10.3390/f14071484 - 20 Jul 2023

Cited by 8 | Viewed by 2371

Abstract

Infestations or parasitism by forestry pests can lead to adverse consequences for tree growth, development, and overall tree quality, ultimately resulting in ecological degradation. The identification and localization of forestry pests are of utmost importance for effective pest control within forest ecosystems. To [...] Read more.

Infestations or parasitism by forestry pests can lead to adverse consequences for tree growth, development, and overall tree quality, ultimately resulting in ecological degradation. The identification and localization of forestry pests are of utmost importance for effective pest control within forest ecosystems. To tackle the challenges posed by variations in pest poses and similarities between different classes, this study introduced a novel end-to-end pest detection algorithm that leverages deep convolutional neural networks (CNNs) and a transfer learning technique. The basic architecture of the method is YOLOv5s, and the C2f module is adopted to replace part of the C3 module to obtain richer gradient information. In addition, the DyHead module is applied to improve the size, task, and spatial awareness of the model. To optimize network parameters and enhance pest detection ability, the model is initially trained using an agricultural pest dataset and subsequently fine-tuned with the forestry pest dataset. A comparative analysis was performed between the proposed method and other mainstream target detection approaches, including YOLOv4-Tiny, YOLOv6, YOLOv7, YOLOv8, and Faster RCNN. The experimental results demonstrated impressive performance in detecting 31 types of forestry pests, achieving a detection precision of 98.1%, recall of 97.5%, and [email protected]:.95 of 88.1%. Significantly, our method outperforms all the compared target detection methods, showcasing a minimum improvement of 2.1% in [email protected]:.95. The model has shown robustness and effectiveness in accurately detecting various pests. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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14 pages, 5085 KiB

Open AccessArticle

Experimental Study of Surface Roughness of Pine Wood by High-Speed Milling

by Chunmei Yang, Yaqiang Ma, Tongbin Liu, Yucheng Ding and Wen Qu

Forests 2023, 14(6), 1275; https://doi.org/10.3390/f14061275 - 20 Jun 2023

Cited by 1 | Viewed by 1820

Abstract

The surface roughness of wood has a great influence on its performance and is a very important indicator in processing and manufacturing. In this paper, we use the central composite design experiment (CCD experiment) and artificial neural network (ANN) model to study the [...] Read more.

The surface roughness of wood has a great influence on its performance and is a very important indicator in processing and manufacturing. In this paper, we use the central composite design experiment (CCD experiment) and artificial neural network (ANN) model to study the changing pattern of surface roughness during the high-speed milling process of pine wood. In the CCD experiments, the spindle speed, feed speed, and depth of cut are used as the influencing factors, and the surface roughness is used as the index to analyze the variation law and fit the surface roughness parameter equation. By measuring the chip size in each group in the CCD experiment, the ANN model is used to predict the surface roughness under this machining parameter by measuring the chip size in each test group. The experimental results showed that the mean error of the surface roughness prediction values in the CCD experiment (12.2%) was larger than that of the ANN model (7.8%), and the mean squared error (MSE) of the ANN model was 0.025, the mean absolute percentage error(MAPE) was 0.01, and the coefficient of determination R² was 0.95. Compared with the CCD experiment, the ANN model had a higher prediction accuracy. The results of this paper can provide some guidance for the prediction of surface roughness during wood processing. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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14 pages, 7992 KiB

Open AccessArticle

Power Compensation Strategy and Experiment of Large Seedling Tree Planter Based on Energy Storage Flywheel

by Binhai Zhu, Jiuqing Liu, Chunmei Yang, Wen Qu and Peng Ding

Forests 2023, 14(5), 1039; https://doi.org/10.3390/f14051039 - 18 May 2023

Cited by 2 | Viewed by 1579

Abstract

The intermittent hole-digging tree-planting machine shows a periodic short-time peak load law in planting operation, and the operation process is “idling” for small loads most of the time, leading to large torque fluctuations in the transmission system, unscientific power matching, and high energy [...] Read more.

The intermittent hole-digging tree-planting machine shows a periodic short-time peak load law in planting operation, and the operation process is “idling” for small loads most of the time, leading to large torque fluctuations in the transmission system, unscientific power matching, and high energy consumption. To solve the above problems, this article proposes to use a series of energy-saving flywheels in the transmission system of the tree planting machine. On the premise of obtaining holes that meet the target young tree planting requirements, the optimal power compensation strategy for the flywheel system of the tree planting machine is studied to reduce torque fluctuations in the power transmission system, use smaller power drive units, and save energy. Firstly, the nonlinear multi-body dynamics simulation model of soil cutting by the hole-digging component is established. The boundary and contact conditions are set to simulate the power consumption of the hole-digging component at three rotating speeds. Based on the simulation results, the flywheel power compensation strategy is discussed, and the torque fluctuation of the flywheel balance system is analyzed. The results showed that the higher the speed, the greater the power consumption. The power value suddenly increased from 17.82 kW (1.28 s) to 27.93 kW (1.43 s) when the speed was 220 r/min. Then, the power value rapidly decreased, and the power consumption presented a short-term peak feature. The transmission system’s maximum input power is determined as 17.82 kW according to the various simulated power consumption characteristics. The part exceeding the power consumption is compensated by the energy storage flywheel. The total compensation energy was 2382.5 J. After the flywheel system was involved, the maximum output power of the tractor power output shaft decreased by 36.2%, and the peak torque decreased from 445.7 N·m to 285.1 N·m. The power consumption obtained from the field test and simulation was similar, but the energy required to overcome peak load was jointly provided by the flywheel and the engine. The actual input power of the power output shaft during the energy release period of the flywheel system was 18.51 kW when the rotating speed of the hole-digging component was 220 r/min, and the relative error with the simulation value was 2.43%. The measured actual speed reduction of the flywheel system was 8.9%. After installing an energy storage flywheel in the transmission system of the tree planting machine, the output power of the power unit can be stabilized. Tree planting machines can be equipped with smaller power units, which can reduce energy consumption and exhaust emissions. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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18 pages, 12927 KiB

Open AccessArticle

Study of the Movement of Chips during Pine Wood Milling

by Chunmei Yang, Tongbin Liu, Yaqiang Ma, Wen Qu, Yucheng Ding, Tao Zhang and Wenlong Song

Forests 2023, 14(4), 849; https://doi.org/10.3390/f14040849 - 20 Apr 2023

Cited by 2 | Viewed by 1711

Abstract

Circumferential milling is used in wood processing, yet it generates vast quantities of dust and chips in a single pass, highlighting the need to predict chip dispersion and prevent associated hazards. This article presents findings from a theoretical and experimental analysis of chip [...] Read more.

Circumferential milling is used in wood processing, yet it generates vast quantities of dust and chips in a single pass, highlighting the need to predict chip dispersion and prevent associated hazards. This article presents findings from a theoretical and experimental analysis of chip size and kinematics of pine wood during cutting. A chip diffusion boundary surface model was established and its key parameters were determined through CCD testing. Results reveal that chip diffusion can be divided into three distinct areas based on motion state: main diffusion, random diffusion, and vortex. Notably, spindle speed and feed rate are most influential on the orthogonal diffusion angle of the main diffusion zone, whereas cutting depth most heavily impacts the top view diffusion angle. Chip scattering on the table showed an exponential increase in average chip size with sampling distance, whereas the boundary surface model accurately characterizes chip motion and demonstrates a reasonable degree of reliability, offering potential in predicting chip morphology and diffusion state. This model has important implications for wood milling practices, particularly in controlling chip dispersion. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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Review

Jump to: Research

21 pages, 14136 KiB

Open AccessReview

Research Hotspots and Frontier Prospects in the Field of Agroforestry Picking Robots in China—Cite Space Bibliographic Analysis

by Na Jia, Hangyu Zhang, Haoshu Gao and Jiuqing Liu

Forests 2023, 14(9), 1874; https://doi.org/10.3390/f14091874 - 14 Sep 2023

Cited by 2 | Viewed by 1339

Abstract

The research on picking robots is vital to the transformation and upgrading of the agroforestry industry and the revitalization and development of rural areas. This paper examines the research field of agroforestry picking robots by meticulously combing and analyzing 623 CNKI and 648 [...] Read more.

The research on picking robots is vital to the transformation and upgrading of the agroforestry industry and the revitalization and development of rural areas. This paper examines the research field of agroforestry picking robots by meticulously combing and analyzing 623 CNKI and 648 WoS core literature from 2004 to 2022 selected in China Knowledge Network (CNKI) and Web of Science (WoS) databases using Cite Space 6.1R3 software. The analysis includes the quantity of literature, issuing countries, organizations, keywords, keyword clustering, emerging terms, etc. On this basis, research hotspots in the field of agroforestry picking robots are identified, such as research based on the identification of picking targets, the control of motion planning, structural design and simulation, and the planning of walking paths. This paper analyzes and discusses these research hotspots and main lines, providing a reference for future studies in this field. This bibliometric approach can provide comprehensive literature information for research in related fields, as well as identify and summarize the major research hotspots in a shorter time, allowing new researchers to enter the field more quickly and obtain more valuable scientific information. Full article

(This article belongs to the Special Issue New Development of Smart Forestry: Machine and Automation)

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