Pub Date : 2023-10-31DOI: 10.1186/s10033-023-00954-x
Haibo Wang, Zipeng Wang, Yu Yan, Yuanhui Xu
Abstract The forming limit diagram plays an important role in predicting the forming limit of sheet metals. Previous studies have shown that, the method to construct the forming limit diagram based on instability theory of the original shear failure criterion is effective and simple. The original shear instability criterion can accurately predict the left area of the forming limit diagram but not the right area. In this study, in order to improve the accuracy of the original shear failure criterion, a modified shear failure criterion was proposed based on in-depth analysis of the original shear failure criterion. The detailed improvement strategies of the shear failure criterion and the complete calculation process are given. Based on the modified shear failure criterion and different constitutive equations, the theoretical forming limit of TRIP780 steel and 5754O aluminum alloy sheet metals are calculated. By comparing the theoretical and experimental results, it is shown that proposed modified shear failure criterion can predict the right area of forming limit more reasonably than the original shear failure criterion. The effect of the pre-strain and constitutive equation on the forming limits are also analyzed in depth. The modified shear failure criterion proposed in this study provides an alternative and reliable method to predict forming limit of sheet metals.
{"title":"Prediction and Verification of Forming Limit Diagrams Based on a Modified Shear Failure Criterion","authors":"Haibo Wang, Zipeng Wang, Yu Yan, Yuanhui Xu","doi":"10.1186/s10033-023-00954-x","DOIUrl":"https://doi.org/10.1186/s10033-023-00954-x","url":null,"abstract":"Abstract The forming limit diagram plays an important role in predicting the forming limit of sheet metals. Previous studies have shown that, the method to construct the forming limit diagram based on instability theory of the original shear failure criterion is effective and simple. The original shear instability criterion can accurately predict the left area of the forming limit diagram but not the right area. In this study, in order to improve the accuracy of the original shear failure criterion, a modified shear failure criterion was proposed based on in-depth analysis of the original shear failure criterion. The detailed improvement strategies of the shear failure criterion and the complete calculation process are given. Based on the modified shear failure criterion and different constitutive equations, the theoretical forming limit of TRIP780 steel and 5754O aluminum alloy sheet metals are calculated. By comparing the theoretical and experimental results, it is shown that proposed modified shear failure criterion can predict the right area of forming limit more reasonably than the original shear failure criterion. The effect of the pre-strain and constitutive equation on the forming limits are also analyzed in depth. The modified shear failure criterion proposed in this study provides an alternative and reliable method to predict forming limit of sheet metals.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135870613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-27DOI: 10.1186/s10033-023-00957-8
Jingang Sun, Changhe Li, Zongming Zhou, Bo Liu, Yanbin Zhang, Min Yang, Teng Gao, Mingzheng Liu, Xin Cui, Benkai Li, Runze Li, Yusuf Suleiman Dambatta, Shubham Sharma
Abstract Micro-grinding with a spherical grinding head has been deemed an indispensable method in high-risk surgeries, such as neurosurgery and spine surgery, where bone grinding has long been plagued by the technical bottleneck of mechanical stress-induced crack damage. In response to this challenge, the ultrasound-assisted biological bone micro-grinding novel process with a spherical grinding head has been proposed by researchers. Force modeling is a prerequisite for process parameter determination in orthopedic surgery, and the difficulty in establishing and accurately predicting bone micro-grinding force prediction models is due to the geometric distribution of abrasive grains and the dynamic changes in geometry and kinematics during the cutting process. In addressing these critical needs and technical problems, the shape and protrusion heights of the wear particle of the spherical grinding head were first studied, and the gradual rule of the contact arc length under the action of high-speed rotating ultrasonic vibration was proposed. Second, the mathematical model of the maximum thickness of undeformed chips under ultrasonic vibration of the spherical grinding head was established. Results showed that ultrasonic vibration can reduce the maximum thickness of undeformed chips and increase the range of ductile and bone meal removals, revealing the mechanism of reducing grinding force. Further, the dynamic grinding behavior of different layers of abrasive particles under different instantaneous interaction states was studied. Finally, a prediction model of micro-grinding force was established in accordance with the relationship between grinding force and cutting depth, revealing the mechanism of micro-grinding force transfer under ultrasonic vibration. The theoretical model’s average deviations are 10.37% in x -axis direction, 6.85% in y -axis direction, and 7.81% in z -axis direction compared with the experimental results. This study provides theoretical guidance and technical support for clinical bone micro-grinding.
{"title":"Material Removal Mechanism and Force Modeling in Ultrasonic Vibration-Assisted Micro-Grinding Biological Bone","authors":"Jingang Sun, Changhe Li, Zongming Zhou, Bo Liu, Yanbin Zhang, Min Yang, Teng Gao, Mingzheng Liu, Xin Cui, Benkai Li, Runze Li, Yusuf Suleiman Dambatta, Shubham Sharma","doi":"10.1186/s10033-023-00957-8","DOIUrl":"https://doi.org/10.1186/s10033-023-00957-8","url":null,"abstract":"Abstract Micro-grinding with a spherical grinding head has been deemed an indispensable method in high-risk surgeries, such as neurosurgery and spine surgery, where bone grinding has long been plagued by the technical bottleneck of mechanical stress-induced crack damage. In response to this challenge, the ultrasound-assisted biological bone micro-grinding novel process with a spherical grinding head has been proposed by researchers. Force modeling is a prerequisite for process parameter determination in orthopedic surgery, and the difficulty in establishing and accurately predicting bone micro-grinding force prediction models is due to the geometric distribution of abrasive grains and the dynamic changes in geometry and kinematics during the cutting process. In addressing these critical needs and technical problems, the shape and protrusion heights of the wear particle of the spherical grinding head were first studied, and the gradual rule of the contact arc length under the action of high-speed rotating ultrasonic vibration was proposed. Second, the mathematical model of the maximum thickness of undeformed chips under ultrasonic vibration of the spherical grinding head was established. Results showed that ultrasonic vibration can reduce the maximum thickness of undeformed chips and increase the range of ductile and bone meal removals, revealing the mechanism of reducing grinding force. Further, the dynamic grinding behavior of different layers of abrasive particles under different instantaneous interaction states was studied. Finally, a prediction model of micro-grinding force was established in accordance with the relationship between grinding force and cutting depth, revealing the mechanism of micro-grinding force transfer under ultrasonic vibration. The theoretical model’s average deviations are 10.37% in x -axis direction, 6.85% in y -axis direction, and 7.81% in z -axis direction compared with the experimental results. This study provides theoretical guidance and technical support for clinical bone micro-grinding.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136261775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-24DOI: 10.1186/s10033-023-00932-3
Liman Yang, Xuze Guo, Jianfu Chen, Yixuan Wang, Huaixiang Ma, Yunhua Li, Zhiguo Yang, Yan Shi
Abstract Shield machines are currently the main tool for underground tunnel construction. Due to the complexity and variability of the underground construction environment, it is necessary to accurately identify the ground in real-time during the tunnel construction process to match and adjust the tunnel parameters according to the geological conditions to ensure construction safety. Compared with the traditional method of stratum identification based on staged drilling sampling, the real-time stratum identification method based on construction data has the advantages of low cost and high precision. Due to the huge amount of sensor data of the ultra-large diameter mud-water balance shield machine, in order to balance the identification time and recognition accuracy of the formation, it is necessary to screen the multivariate data features collected by hundreds of sensors. In response to this problem, this paper proposes a voting-based feature extraction method (VFS), which integrates multiple feature extraction algorithms FSM, and the frequency of each feature in all feature extraction algorithms is the basis for voting. At the same time, in order to verify the wide applicability of the method, several commonly used classification models are used to train and test the obtained effective feature data, and the model accuracy and recognition time are used as evaluation indicators, and the classification with the best combination with VFS is obtained. The experimental results of shield machine data of 6 different geological structures show that the average accuracy of 13 features obtained by VFS combined with different classification algorithms is 91%; among them, the random forest model takes less time and has the highest recognition accuracy, reaching 93%, showing best compatibility with VFS. Therefore, the VFS algorithm proposed in this paper has high reliability and wide applicability for stratum identification in the process of tunnel construction, and can be matched with a variety of classifier algorithms. By combining 13 features selected from shield machine data features with random forest, the identification of the construction stratum environment of shield tunnels can be well realized, and further theoretical guidance for underground engineering construction can be provided.
{"title":"Vote-Based Feature Selection Method for Stratigraphic Recognition in Tunnelling Process of Shield Machine","authors":"Liman Yang, Xuze Guo, Jianfu Chen, Yixuan Wang, Huaixiang Ma, Yunhua Li, Zhiguo Yang, Yan Shi","doi":"10.1186/s10033-023-00932-3","DOIUrl":"https://doi.org/10.1186/s10033-023-00932-3","url":null,"abstract":"Abstract Shield machines are currently the main tool for underground tunnel construction. Due to the complexity and variability of the underground construction environment, it is necessary to accurately identify the ground in real-time during the tunnel construction process to match and adjust the tunnel parameters according to the geological conditions to ensure construction safety. Compared with the traditional method of stratum identification based on staged drilling sampling, the real-time stratum identification method based on construction data has the advantages of low cost and high precision. Due to the huge amount of sensor data of the ultra-large diameter mud-water balance shield machine, in order to balance the identification time and recognition accuracy of the formation, it is necessary to screen the multivariate data features collected by hundreds of sensors. In response to this problem, this paper proposes a voting-based feature extraction method (VFS), which integrates multiple feature extraction algorithms FSM, and the frequency of each feature in all feature extraction algorithms is the basis for voting. At the same time, in order to verify the wide applicability of the method, several commonly used classification models are used to train and test the obtained effective feature data, and the model accuracy and recognition time are used as evaluation indicators, and the classification with the best combination with VFS is obtained. The experimental results of shield machine data of 6 different geological structures show that the average accuracy of 13 features obtained by VFS combined with different classification algorithms is 91%; among them, the random forest model takes less time and has the highest recognition accuracy, reaching 93%, showing best compatibility with VFS. Therefore, the VFS algorithm proposed in this paper has high reliability and wide applicability for stratum identification in the process of tunnel construction, and can be matched with a variety of classifier algorithms. By combining 13 features selected from shield machine data features with random forest, the identification of the construction stratum environment of shield tunnels can be well realized, and further theoretical guidance for underground engineering construction can be provided.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"55 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135266646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.1186/s10033-023-00960-z
Siqi Shi, Shijie Jin, Donghui Zhang, Jingyu Liao, Dongxin Fu, Li Lin
Abstract Ultrasonic testing (UT) is increasingly combined with machine learning (ML) techniques for intelligently identifying damage. Extracting significant features from UT data is essential for efficient defect characterization. Moreover, the hidden physics behind ML is unexplained, reducing the generalization capability and versatility of ML methods in UT. In this paper, a generally applicable ML framework based on the model interpretation strategy is proposed to improve the detection accuracy and computational efficiency of UT. Firstly, multi-domain features are extracted from the UT signals with signal processing techniques to construct an initial feature space. Subsequently, a feature selection method based on model interpretable strategy (FS-MIS) is innovatively developed by integrating Shapley additive explanation (SHAP), filter method, embedded method and wrapper method. The most effective ML model and the optimal feature subset with better correlation to the target defects are determined self-adaptively. The proposed framework is validated by identifying and locating side-drilled holes (SDHs) with 0.5 λ central distance and different depths. An ultrasonic array probe is adopted to acquire FMC datasets from several aluminum alloy specimens containing two SDHs by experiments. The optimal feature subset selected by FS-MIS is set as the input of the chosen ML model to train and predict the times of arrival (ToAs) of the scattered waves emitted by adjacent SDHs. The experimental results demonstrate that the relative errors of the predicted ToAs are all below 3.67% with an average error of 0.25%, significantly improving the time resolution of UT signals. On this basis, the predicted ToAs are assigned to the corresponding original signals for decoupling overlapped pulse-echoes and reconstructing high-resolution FMC datasets. The imaging resolution is enhanced to 0.5 λ by implementing the total focusing method (TFM). The relative errors of hole depths and central distance are no more than 0.51% and 3.57%, respectively. Finally, the superior performance of the proposed FS-MIS is validated by comparing it with initial feature space and conventional dimensionality reduction techniques.
{"title":"Improving Ultrasonic Testing by Using Machine Learning Framework Based on Model Interpretation Strategy","authors":"Siqi Shi, Shijie Jin, Donghui Zhang, Jingyu Liao, Dongxin Fu, Li Lin","doi":"10.1186/s10033-023-00960-z","DOIUrl":"https://doi.org/10.1186/s10033-023-00960-z","url":null,"abstract":"Abstract Ultrasonic testing (UT) is increasingly combined with machine learning (ML) techniques for intelligently identifying damage. Extracting significant features from UT data is essential for efficient defect characterization. Moreover, the hidden physics behind ML is unexplained, reducing the generalization capability and versatility of ML methods in UT. In this paper, a generally applicable ML framework based on the model interpretation strategy is proposed to improve the detection accuracy and computational efficiency of UT. Firstly, multi-domain features are extracted from the UT signals with signal processing techniques to construct an initial feature space. Subsequently, a feature selection method based on model interpretable strategy (FS-MIS) is innovatively developed by integrating Shapley additive explanation (SHAP), filter method, embedded method and wrapper method. The most effective ML model and the optimal feature subset with better correlation to the target defects are determined self-adaptively. The proposed framework is validated by identifying and locating side-drilled holes (SDHs) with 0.5 λ central distance and different depths. An ultrasonic array probe is adopted to acquire FMC datasets from several aluminum alloy specimens containing two SDHs by experiments. The optimal feature subset selected by FS-MIS is set as the input of the chosen ML model to train and predict the times of arrival (ToAs) of the scattered waves emitted by adjacent SDHs. The experimental results demonstrate that the relative errors of the predicted ToAs are all below 3.67% with an average error of 0.25%, significantly improving the time resolution of UT signals. On this basis, the predicted ToAs are assigned to the corresponding original signals for decoupling overlapped pulse-echoes and reconstructing high-resolution FMC datasets. The imaging resolution is enhanced to 0.5 λ by implementing the total focusing method (TFM). The relative errors of hole depths and central distance are no more than 0.51% and 3.57%, respectively. Finally, the superior performance of the proposed FS-MIS is validated by comparing it with initial feature space and conventional dimensionality reduction techniques.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"49 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135405464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract With the increasing attention to the state and role of people in intelligent manufacturing, there is a strong demand for human-cyber-physical systems (HCPS) that focus on human-robot interaction. The existing intelligent manufacturing system cannot satisfy efficient human-robot collaborative work. However, unlike machines equipped with sensors, human characteristic information is difficult to be perceived and digitized instantly. In view of the high complexity and uncertainty of the human body, this paper proposes a framework for building a human digital twin (HDT) model based on multimodal data and expounds on the key technologies. Data acquisition system is built to dynamically acquire and update the body state data and physiological data of the human body and realize the digital expression of multi-source heterogeneous human body information. A bidirectional long short-term memory and convolutional neural network (BiLSTM-CNN) based network is devised to fuse multimodal human data and extract the spatiotemporal features, and the human locomotion mode identification is taken as an application case. A series of optimization experiments are carried out to improve the performance of the proposed BiLSTM-CNN-based network model. The proposed model is compared with traditional locomotion mode identification models. The experimental results proved the superiority of the HDT framework for human locomotion mode identification.
{"title":"Construction of Human Digital Twin Model Based on Multimodal Data and Its Application in Locomotion Mode Identification","authors":"Ruirui Zhong, Bingtao Hu, Yixiong Feng, Hao Zheng, Zhaoxi Hong, Shanhe Lou, Jianrong Tan","doi":"10.1186/s10033-023-00951-0","DOIUrl":"https://doi.org/10.1186/s10033-023-00951-0","url":null,"abstract":"Abstract With the increasing attention to the state and role of people in intelligent manufacturing, there is a strong demand for human-cyber-physical systems (HCPS) that focus on human-robot interaction. The existing intelligent manufacturing system cannot satisfy efficient human-robot collaborative work. However, unlike machines equipped with sensors, human characteristic information is difficult to be perceived and digitized instantly. In view of the high complexity and uncertainty of the human body, this paper proposes a framework for building a human digital twin (HDT) model based on multimodal data and expounds on the key technologies. Data acquisition system is built to dynamically acquire and update the body state data and physiological data of the human body and realize the digital expression of multi-source heterogeneous human body information. A bidirectional long short-term memory and convolutional neural network (BiLSTM-CNN) based network is devised to fuse multimodal human data and extract the spatiotemporal features, and the human locomotion mode identification is taken as an application case. A series of optimization experiments are carried out to improve the performance of the proposed BiLSTM-CNN-based network model. The proposed model is compared with traditional locomotion mode identification models. The experimental results proved the superiority of the HDT framework for human locomotion mode identification.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135617606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The service cycle and dynamic performance of structural parts are affected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of the robot does not coincide with the theoretical track when the weld is ground offline, resulting in poor workpiece surface quality. Considering these problems, in this study, a vision sensing-based online correction system for robotic weld grinding was developed. The system mainly included three subsystems: weld feature extraction, grinding, and robot real-time control. The grinding equipment was first set as a substation for the robot using the WorkVisual software. The input/output (I/O) ports for communication between the robot and the grinding equipment were configured via the I/O mapping function to enable the robot to control the grinding equipment (start, stop, and speed control). Subsequently, the Ethernet KRL software package was used to write the data interaction structure to realize real-time communication between the robot and the laser vision system. To correct the measurement error caused by the bending deformation of the workpiece, we established a surface profile model of the base material in the weld area using a polynomial fitting algorithm to compensate for the measurement data. The corrected extracted weld width and height errors were reduced by 2.01% and 9.3%, respectively. Online weld seam extraction and correction experiments verified the effectiveness of the system’s correction function, and the system could control the grinding trajectory error within 0.2 mm. The reliability of the system was verified through actual weld grinding experiments. The roughness, Ra, could reach 0.504 µm and the average residual height was within 0.21 mm. In this study, we developed a vision sensing-based online correction system for robotic weld grinding with a good correction effect and high robustness.
{"title":"Vision Sensing-Based Online Correction System for Robotic Weld Grinding","authors":"Jimin Ge, Zhaohui Deng, Shuixian Wang, Zhongyang Li, Wei Liu, Jiaxu Nie","doi":"10.1186/s10033-023-00955-w","DOIUrl":"https://doi.org/10.1186/s10033-023-00955-w","url":null,"abstract":"Abstract The service cycle and dynamic performance of structural parts are affected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of the robot does not coincide with the theoretical track when the weld is ground offline, resulting in poor workpiece surface quality. Considering these problems, in this study, a vision sensing-based online correction system for robotic weld grinding was developed. The system mainly included three subsystems: weld feature extraction, grinding, and robot real-time control. The grinding equipment was first set as a substation for the robot using the WorkVisual software. The input/output (I/O) ports for communication between the robot and the grinding equipment were configured via the I/O mapping function to enable the robot to control the grinding equipment (start, stop, and speed control). Subsequently, the Ethernet KRL software package was used to write the data interaction structure to realize real-time communication between the robot and the laser vision system. To correct the measurement error caused by the bending deformation of the workpiece, we established a surface profile model of the base material in the weld area using a polynomial fitting algorithm to compensate for the measurement data. The corrected extracted weld width and height errors were reduced by 2.01% and 9.3%, respectively. Online weld seam extraction and correction experiments verified the effectiveness of the system’s correction function, and the system could control the grinding trajectory error within 0.2 mm. The reliability of the system was verified through actual weld grinding experiments. The roughness, Ra, could reach 0.504 µm and the average residual height was within 0.21 mm. In this study, we developed a vision sensing-based online correction system for robotic weld grinding with a good correction effect and high robustness.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135617262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract To satisfy the requirements for the precise formation of large-scale high-performance lightweight components with inner ring reinforcement, a new multidirectional loading rotary extrusion forming technology is developed to match the linear motion with the rotary motion and actively increases the strong shear force. Its principle is that the radial force and rotating torque increase when the blank is axially extruded and loaded. Through the synergistic action of axial, radial, and rotating motions, the orderly flow of metal is controlled, and the cumulative severe plastic deformation (SPD) of an “uplift-trowel” micro-area is generated. Consequently, materials are uniformly strengthened and toughened. Simultaneously, through the continuous deformation of a punch “ellipse-circle,” a high reinforcement component is grown on the cylinder wall to achieve the high-quality formation of cylindrical parts or the inner-ring-reinforcement components. Additionally, the effective strain increases with rotation speed, and the maximum intensity on the basal plane decreases as the number of revolutions increase. The punch structure also affects the axial extrusion loading and equivalent plastic strain. Thus, the proposed technology enriches the plastic forming theory and widens the application field of plastic forming. Furthermore, the formed large-scale high-performance inner-ring-stiffened magnesium components have been successfully verified in aerospace equipment, thereby solving the problems of integral forming and severe deformation strengthening and toughening. The developed technology has good prospects for mass production and application.
{"title":"New Technology of Multidirectional Loading Rotary Extrusion","authors":"Zhimin Zhang, Yong Xue, Xing Zhang, Beibei Dong, Mei Cheng, Zhe Chen","doi":"10.1186/s10033-023-00942-1","DOIUrl":"https://doi.org/10.1186/s10033-023-00942-1","url":null,"abstract":"Abstract To satisfy the requirements for the precise formation of large-scale high-performance lightweight components with inner ring reinforcement, a new multidirectional loading rotary extrusion forming technology is developed to match the linear motion with the rotary motion and actively increases the strong shear force. Its principle is that the radial force and rotating torque increase when the blank is axially extruded and loaded. Through the synergistic action of axial, radial, and rotating motions, the orderly flow of metal is controlled, and the cumulative severe plastic deformation (SPD) of an “uplift-trowel” micro-area is generated. Consequently, materials are uniformly strengthened and toughened. Simultaneously, through the continuous deformation of a punch “ellipse-circle,” a high reinforcement component is grown on the cylinder wall to achieve the high-quality formation of cylindrical parts or the inner-ring-reinforcement components. Additionally, the effective strain increases with rotation speed, and the maximum intensity on the basal plane decreases as the number of revolutions increase. The punch structure also affects the axial extrusion loading and equivalent plastic strain. Thus, the proposed technology enriches the plastic forming theory and widens the application field of plastic forming. Furthermore, the formed large-scale high-performance inner-ring-stiffened magnesium components have been successfully verified in aerospace equipment, thereby solving the problems of integral forming and severe deformation strengthening and toughening. The developed technology has good prospects for mass production and application.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135730096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Kinematic calibration is a reliable way to improve the accuracy of parallel manipulators, while the error model dramatically affects the accuracy, reliability, and stability of identification results. In this paper, a comparison study on kinematic calibration for a 3-DOF parallel manipulator with three error models is presented to investigate the relative merits of different error modeling methods. The study takes into consideration the inverse-kinematic error model, which ignores all passive joint errors, the geometric-constraint error model, which is derived by special geometric constraints of the studied RPR-equivalent parallel manipulator, and the complete-minimal error model, which meets the complete, minimal, and continuous criteria. This comparison focuses on aspects such as modeling complexity, identification accuracy, the impact of noise uncertainty, and parameter identifiability. To facilitate a more intuitive comparison, simulations are conducted to draw conclusions in certain aspects, including accuracy, the influence of the S joint, identification with noises, and sensitivity indices. The simulations indicate that the complete-minimal error model exhibits the lowest residual values, and all error models demonstrate stability considering noises. Hereafter, an experiment is conducted on a prototype using a laser tracker, providing further insights into the differences among the three error models. The results show that the residual errors of this machine tool are significantly improved according to the identified parameters, and the complete-minimal error model can approach the measurements by nearly 90% compared to the inverse-kinematic error model. The findings pertaining to the model process, complexity, and limitations are also instructive for other parallel manipulators.
{"title":"A Comparative Study on Kinematic Calibration for a 3-DOF Parallel Manipulator Using the Complete-Minimal, Inverse-Kinematic and Geometric-Constraint Error Models","authors":"Haiyu Wu, Lingyu Kong, Qinchuan Li, Hao Wang, Genliang Chen","doi":"10.1186/s10033-023-00940-3","DOIUrl":"https://doi.org/10.1186/s10033-023-00940-3","url":null,"abstract":"Abstract Kinematic calibration is a reliable way to improve the accuracy of parallel manipulators, while the error model dramatically affects the accuracy, reliability, and stability of identification results. In this paper, a comparison study on kinematic calibration for a 3-DOF parallel manipulator with three error models is presented to investigate the relative merits of different error modeling methods. The study takes into consideration the inverse-kinematic error model, which ignores all passive joint errors, the geometric-constraint error model, which is derived by special geometric constraints of the studied RPR-equivalent parallel manipulator, and the complete-minimal error model, which meets the complete, minimal, and continuous criteria. This comparison focuses on aspects such as modeling complexity, identification accuracy, the impact of noise uncertainty, and parameter identifiability. To facilitate a more intuitive comparison, simulations are conducted to draw conclusions in certain aspects, including accuracy, the influence of the S joint, identification with noises, and sensitivity indices. The simulations indicate that the complete-minimal error model exhibits the lowest residual values, and all error models demonstrate stability considering noises. Hereafter, an experiment is conducted on a prototype using a laser tracker, providing further insights into the differences among the three error models. The results show that the residual errors of this machine tool are significantly improved according to the identified parameters, and the complete-minimal error model can approach the measurements by nearly 90% compared to the inverse-kinematic error model. The findings pertaining to the model process, complexity, and limitations are also instructive for other parallel manipulators.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135884056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-18DOI: 10.1186/s10033-023-00952-z
Zengming Feng, Jinxing Yang, Fei Wang
Abstract As a fundamental component of an automobile engine's timing chain drive system, the hydraulic automatic tensioner significantly enhances fuel economy while minimizing system vibrations and noise. However, there is a noticeable lack of research on automatic hydraulic tensioners. This study presents a comprehensive calculation approach for the principal parameters of a hydraulic automatic tensioner. An effective method, grounded in hydraulics and multibody dynamics, was introduced for estimating the dynamic response of such a tensioner. The simulation model developed for the hydraulic tensioner is characterized by its rapid dynamic response, consistent operation, and high accuracy. The dynamic behavior of the tensioner was analyzed under varying boundary conditions, using sinusoidal signal excitation. It was observed that the maximum damping force increases with a decreasing leakage gap. Conversely, an increase in oil temperature or air content leads to a decrease in the maximum damping force. The reaction forces derived from these calculations align well with experimental results. This calculation and simulation approach offers considerable value for the design of innovative hydraulic tensioners. It not only streamlines the design phase, minimizes the number of trials, and reduces product costs, but also provides robust insights for evaluating the performance of hydraulic tensioners.
{"title":"Dynamic Simulation and Test Verification of Hydraulic Automatic Tensioner for an Engine Timing Chain Drive System","authors":"Zengming Feng, Jinxing Yang, Fei Wang","doi":"10.1186/s10033-023-00952-z","DOIUrl":"https://doi.org/10.1186/s10033-023-00952-z","url":null,"abstract":"Abstract As a fundamental component of an automobile engine's timing chain drive system, the hydraulic automatic tensioner significantly enhances fuel economy while minimizing system vibrations and noise. However, there is a noticeable lack of research on automatic hydraulic tensioners. This study presents a comprehensive calculation approach for the principal parameters of a hydraulic automatic tensioner. An effective method, grounded in hydraulics and multibody dynamics, was introduced for estimating the dynamic response of such a tensioner. The simulation model developed for the hydraulic tensioner is characterized by its rapid dynamic response, consistent operation, and high accuracy. The dynamic behavior of the tensioner was analyzed under varying boundary conditions, using sinusoidal signal excitation. It was observed that the maximum damping force increases with a decreasing leakage gap. Conversely, an increase in oil temperature or air content leads to a decrease in the maximum damping force. The reaction forces derived from these calculations align well with experimental results. This calculation and simulation approach offers considerable value for the design of innovative hydraulic tensioners. It not only streamlines the design phase, minimizes the number of trials, and reduces product costs, but also provides robust insights for evaluating the performance of hydraulic tensioners.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135883045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：