Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856224
Ming Li, Manyi Wang, Longmiao Chen, Liuxuan Wei
Due to the small number of samples of the inter-turn short-circuit fault of the current permanent magnet synchronous motor, and the motor working in a high-noise environment, the collected data contains complicated noise. So first the deep residual shrinkage network is pre-trained on the big data simulation dataset. And then to avoid imbalances between real data sets, GAN network is adopted to generate more datasets in this paper. Based on the aforementioned data set, the pretrained network is proposed to denoise the environment and other noise in the data set. And Spatial Dropout layer into the network is introduced to improve the accuracy and convergence speed of fault diagnosis. Experiments show that by combining GAN and DRSN methods for fault diagnosis of unbalanced samples, disturbances such as datasets and reducing environmental noise can be effectively balanced. The diagnostic accuracy is as high as 97.5%.
{"title":"GAN-DRSN based Inter-turn Short Circuit Fault Diagnosis of PMSM","authors":"Ming Li, Manyi Wang, Longmiao Chen, Liuxuan Wei","doi":"10.1109/ICMA54519.2022.9856224","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856224","url":null,"abstract":"Due to the small number of samples of the inter-turn short-circuit fault of the current permanent magnet synchronous motor, and the motor working in a high-noise environment, the collected data contains complicated noise. So first the deep residual shrinkage network is pre-trained on the big data simulation dataset. And then to avoid imbalances between real data sets, GAN network is adopted to generate more datasets in this paper. Based on the aforementioned data set, the pretrained network is proposed to denoise the environment and other noise in the data set. And Spatial Dropout layer into the network is introduced to improve the accuracy and convergence speed of fault diagnosis. Experiments show that by combining GAN and DRSN methods for fault diagnosis of unbalanced samples, disturbances such as datasets and reducing environmental noise can be effectively balanced. The diagnostic accuracy is as high as 97.5%.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131836064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856051
Defu Zhang, Kangli Wang, Jianfeng Gao, Xiuming Che
In order to improve the intelligent energy efficiency management of ships, evaluate the fuel utilization efficiency of marine diesel engine. In this paper, a fuel consumption model of marine diesel engine based on autoencoder and deep neural network is established, and the autoencoder is used to perform nonlinear dimensionality reduction on the data to obtain more valuable data features, thereby improving the accuracy of the model. The model is verified and compared using the sailing parameters, environmental parameters and fuel consumption of the actual ship during normal sailing. The accuracy rate of the model established in this paper reaches 95.19%, and the results show that the model in this paper can meet the prediction and evaluation analysis of the energy consumption of the marine diesel engine.
{"title":"Autoencoder and Deep Neural Network based Energy Consumption Analysis of Marine Diesel Engine","authors":"Defu Zhang, Kangli Wang, Jianfeng Gao, Xiuming Che","doi":"10.1109/ICMA54519.2022.9856051","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856051","url":null,"abstract":"In order to improve the intelligent energy efficiency management of ships, evaluate the fuel utilization efficiency of marine diesel engine. In this paper, a fuel consumption model of marine diesel engine based on autoencoder and deep neural network is established, and the autoencoder is used to perform nonlinear dimensionality reduction on the data to obtain more valuable data features, thereby improving the accuracy of the model. The model is verified and compared using the sailing parameters, environmental parameters and fuel consumption of the actual ship during normal sailing. The accuracy rate of the model established in this paper reaches 95.19%, and the results show that the model in this paper can meet the prediction and evaluation analysis of the energy consumption of the marine diesel engine.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134433680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856139
Juan Li, Jinyu Su
When using particle swarm optimization (PSO) to realize the global path planning of the robot, premature convergence and falling into the local optimum often occur. Therefore, an improved second-order PSO is used to improve premature convergence and analyze its stability. The logistic function relationship is established between the inertia weight and the learning factors. Using linearly decreasing inertia weight and adaptive learning factors, making the inertia weight change together with the learning factors to change the global or local flight ability to improve the ability to jump out of the local optimum. Through simulation comparison, it is proved that the improved second-order PSO proposed in this paper has the ability to jump out of the local optimum in the global path planning, and at the same time avoids premature convergence, and can also improve the convergence speed of the algorithm, which verifies the effectiveness of the algorithm.
{"title":"Robot Global Path Planning Based on Improved Second-Order PSO Algorithm","authors":"Juan Li, Jinyu Su","doi":"10.1109/ICMA54519.2022.9856139","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856139","url":null,"abstract":"When using particle swarm optimization (PSO) to realize the global path planning of the robot, premature convergence and falling into the local optimum often occur. Therefore, an improved second-order PSO is used to improve premature convergence and analyze its stability. The logistic function relationship is established between the inertia weight and the learning factors. Using linearly decreasing inertia weight and adaptive learning factors, making the inertia weight change together with the learning factors to change the global or local flight ability to improve the ability to jump out of the local optimum. Through simulation comparison, it is proved that the improved second-order PSO proposed in this paper has the ability to jump out of the local optimum in the global path planning, and at the same time avoids premature convergence, and can also improve the convergence speed of the algorithm, which verifies the effectiveness of the algorithm.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133056802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856335
Peijian Qu, Nan Liu, Zhengpeng Qin, Tianbo Jin, Hongze Fu, Zihao Li, Peisheng Sang
In view of the current situation that the per capita cultivated land in agriculture is insufficient, the yield per mu is reduced and the degree of intelligence in the traditional greenhouse is low, A multi-layer intelligent farm with deep learning algorithm is proposed. Firstly, the overall design of the system is described in detail, including multi-layer greenhouse frame, water, fertilizer and medicine integrated machine, two-dimensional interpolation inspection robot, ventilation fan, fluorescent lamp, circulating water curtain; Secondly, the electrical system and cloud control system are designed. Finally, a deep learning network based on YoloV4-Tiny is installed on Raspberry PI to solve the image recognition problem of rose deficiency and insect pests. After a large number of experimental tests, it is found that the speed and accuracy of using YOLOV4-Tiny are improved compared with using YOLOV4. It solves the common problems of difficult to capture objects and slow recognition of features in other types of greenhouse systems, meets the requirements of ensuring good plant growth in different environments, and ensures the high quality and efficient operation of the greenhouse system.
{"title":"Deep learning based detection of plant nutrient deficiency symptom and design of multi-layer greenhouse system","authors":"Peijian Qu, Nan Liu, Zhengpeng Qin, Tianbo Jin, Hongze Fu, Zihao Li, Peisheng Sang","doi":"10.1109/ICMA54519.2022.9856335","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856335","url":null,"abstract":"In view of the current situation that the per capita cultivated land in agriculture is insufficient, the yield per mu is reduced and the degree of intelligence in the traditional greenhouse is low, A multi-layer intelligent farm with deep learning algorithm is proposed. Firstly, the overall design of the system is described in detail, including multi-layer greenhouse frame, water, fertilizer and medicine integrated machine, two-dimensional interpolation inspection robot, ventilation fan, fluorescent lamp, circulating water curtain; Secondly, the electrical system and cloud control system are designed. Finally, a deep learning network based on YoloV4-Tiny is installed on Raspberry PI to solve the image recognition problem of rose deficiency and insect pests. After a large number of experimental tests, it is found that the speed and accuracy of using YOLOV4-Tiny are improved compared with using YOLOV4. It solves the common problems of difficult to capture objects and slow recognition of features in other types of greenhouse systems, meets the requirements of ensuring good plant growth in different environments, and ensures the high quality and efficient operation of the greenhouse system.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132124290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856070
Cheng-peng Yu, Bin Li, Jiaqi Zhu
In this paper, the kinematics of the 3-RRPS parallel mechanism was deeply studied, and the kinematics mathematical model of the parallel mechanism was obtained by using the method of coordinate system transformation. The inverse solution of the parallel mechanism pose was obtained by solving this equation, and the nonlinear equation was obtained from the inverse solution. The forward solution of the attitude of the parallel mechanism was calculated by solving this nonlinear equation with Jacobian matrix and Newton iterative algorithm, which is an approximate solution. Finally, we verified the correctness of the forward kinematics solution through MATLAB.
{"title":"Kinematics Analysis of 3-RRPS Parallel Mechanism","authors":"Cheng-peng Yu, Bin Li, Jiaqi Zhu","doi":"10.1109/ICMA54519.2022.9856070","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856070","url":null,"abstract":"In this paper, the kinematics of the 3-RRPS parallel mechanism was deeply studied, and the kinematics mathematical model of the parallel mechanism was obtained by using the method of coordinate system transformation. The inverse solution of the parallel mechanism pose was obtained by solving this equation, and the nonlinear equation was obtained from the inverse solution. The forward solution of the attitude of the parallel mechanism was calculated by solving this nonlinear equation with Jacobian matrix and Newton iterative algorithm, which is an approximate solution. Finally, we verified the correctness of the forward kinematics solution through MATLAB.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130284824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856377
Juan Li, Ning Fang
Task allocation is a very important part of multi-agent systems. When assigning tasks to one of the agents in multi-agent systems, many constraints need to be considered to achieve optimal allocation results. In this paper, an improved genetic algorithm (GA) is proposed to solve the multi-agent task allocation with time window constraints. Firstly, the mathematical model of task allocation is established, and the constraint problem of time window is analyzed. The penalty function method is used to deal with the constraint condition. Secondly, the improved Large Neighborhood Search (LNS) is added to the local search to increase the diversity of population, which can make the algorithm easier to jump out of local optimum. Then genetic algorithm is used to solve the multi-agent task allocation problem with time window constraints. Finally, the simulation verifies the optimization performance of the improved algorithm.
{"title":"Improved Genetic Algorithm for Multi-agent Task Allocation with Time Windows","authors":"Juan Li, Ning Fang","doi":"10.1109/ICMA54519.2022.9856377","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856377","url":null,"abstract":"Task allocation is a very important part of multi-agent systems. When assigning tasks to one of the agents in multi-agent systems, many constraints need to be considered to achieve optimal allocation results. In this paper, an improved genetic algorithm (GA) is proposed to solve the multi-agent task allocation with time window constraints. Firstly, the mathematical model of task allocation is established, and the constraint problem of time window is analyzed. The penalty function method is used to deal with the constraint condition. Secondly, the improved Large Neighborhood Search (LNS) is added to the local search to increase the diversity of population, which can make the algorithm easier to jump out of local optimum. Then genetic algorithm is used to solve the multi-agent task allocation problem with time window constraints. Finally, the simulation verifies the optimization performance of the improved algorithm.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132338456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856178
Xianhui Liu, Luyuan Liu, Jianqiang Li, Fan Yang
The prefabricated concrete structure is conducive to the development of China’s building industrialization. It is one of the important directions for the development of China’s building structure, of which prestressed concrete structure is an important part of the prefabricated concrete structure. The key technology to achieve prestressed concrete is the tension of the prestressed steel strand. The tensioning process includes: 1 The prestressed steel strand penetrates the tension hole of the tensioning equipment. 2 the tensioning equipment continues to tension the prestressed steel strand. Among them, the perforation process of tension has always been manually realized. At present, industrial intelligence includes all walks of life, and equipment related to construction projects also conform to the development of intelligence. The intelligent tensioning robot proposed in this paper is based on the tensile equipment to add a robotic arm, sensors, etc., which can automatically find tensioning holes to facilitate the perforation process when the prestressed ribs are stretched, with the purpose of improving the efficiency of perforation, improving the safety of the tensioning process, and reducing the dependence of tensile construction on labor. In this article, the method of collecting anchor plate position information is introduced, and the modular program of MODBUS communication based on Delta PLC is provided.
{"title":"Application of MODBUS Communication Protocol in Intelligent Prestress Tension Robot","authors":"Xianhui Liu, Luyuan Liu, Jianqiang Li, Fan Yang","doi":"10.1109/ICMA54519.2022.9856178","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856178","url":null,"abstract":"The prefabricated concrete structure is conducive to the development of China’s building industrialization. It is one of the important directions for the development of China’s building structure, of which prestressed concrete structure is an important part of the prefabricated concrete structure. The key technology to achieve prestressed concrete is the tension of the prestressed steel strand. The tensioning process includes: 1 The prestressed steel strand penetrates the tension hole of the tensioning equipment. 2 the tensioning equipment continues to tension the prestressed steel strand. Among them, the perforation process of tension has always been manually realized. At present, industrial intelligence includes all walks of life, and equipment related to construction projects also conform to the development of intelligence. The intelligent tensioning robot proposed in this paper is based on the tensile equipment to add a robotic arm, sensors, etc., which can automatically find tensioning holes to facilitate the perforation process when the prestressed ribs are stretched, with the purpose of improving the efficiency of perforation, improving the safety of the tensioning process, and reducing the dependence of tensile construction on labor. In this article, the method of collecting anchor plate position information is introduced, and the modular program of MODBUS communication based on Delta PLC is provided.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133833628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856068
Xuesong Zhou, Xiaojie Liu, Youjie Ma, Xing Zhao
The parallel connection of inverters will produce large harmonic circulation, which can be divided into two types according to different causes: load end and power end. For the harmonic circulation generated at the load end, it combines the negative virtual harmonic impedance and adaptive harmonic impedance. For other virtual harmonic impedance, this strategy can minimize the increase of bus voltage drop and harmonic distortion rate caused by adding virtual impedance, and suppress the harmonic circulation without affecting the system stability; For the circulating current generated by different dead time, Linear active disturbance rejection control is used to estimate and compensate the dead time voltage, and the circulating current is suppressed by observer bandwidth and controller bandwidth. Finally, simulation results verify the correctness and effectiveness of the proposed improved control strategy.
{"title":"Harmonic Circulating Current Control of Parallel Inverter Considering Voltage Bus Quality","authors":"Xuesong Zhou, Xiaojie Liu, Youjie Ma, Xing Zhao","doi":"10.1109/ICMA54519.2022.9856068","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856068","url":null,"abstract":"The parallel connection of inverters will produce large harmonic circulation, which can be divided into two types according to different causes: load end and power end. For the harmonic circulation generated at the load end, it combines the negative virtual harmonic impedance and adaptive harmonic impedance. For other virtual harmonic impedance, this strategy can minimize the increase of bus voltage drop and harmonic distortion rate caused by adding virtual impedance, and suppress the harmonic circulation without affecting the system stability; For the circulating current generated by different dead time, Linear active disturbance rejection control is used to estimate and compensate the dead time voltage, and the circulating current is suppressed by observer bandwidth and controller bandwidth. Finally, simulation results verify the correctness and effectiveness of the proposed improved control strategy.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122871052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856343
Jiaqi Wang, Dongmei Wu, W. Dong, Yongzhuo Gao
While many challenges remain with respect to the mechanical design of the lower limb exoskeleton, it is equally challenging and important to develop effective control strategies. The exoskeleton is a highly human-robot coupled system with a complex dynamic model and working environment, so it is crucial that the controller works in concert with the user intention without relying on imprecise models. This paper proposes a motion controller for a lower limb exoskeleton, aiming to perform collaborative squatting assistance with efficiency and flexibility. This control strategy is designed for our exoskeleton which is equipped with a force sensor on the back. The high-level control is a force-velocity admittance model estimating the human intention by the interaction force, and the low-level control is based on PD closed-loop velocity control with gravity compensation. Through experimental studies conducted with our exoskeleton, the feasibility and effectiveness of the control strategy are demonstrated.
{"title":"A Control Strategy for Squat Assistance of Lower Limb Exoskeleton with Back Sensing","authors":"Jiaqi Wang, Dongmei Wu, W. Dong, Yongzhuo Gao","doi":"10.1109/ICMA54519.2022.9856343","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856343","url":null,"abstract":"While many challenges remain with respect to the mechanical design of the lower limb exoskeleton, it is equally challenging and important to develop effective control strategies. The exoskeleton is a highly human-robot coupled system with a complex dynamic model and working environment, so it is crucial that the controller works in concert with the user intention without relying on imprecise models. This paper proposes a motion controller for a lower limb exoskeleton, aiming to perform collaborative squatting assistance with efficiency and flexibility. This control strategy is designed for our exoskeleton which is equipped with a force sensor on the back. The high-level control is a force-velocity admittance model estimating the human intention by the interaction force, and the low-level control is based on PD closed-loop velocity control with gravity compensation. Through experimental studies conducted with our exoskeleton, the feasibility and effectiveness of the control strategy are demonstrated.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124023181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856354
Q. Pan, Sa Li, Peilun Li, Lang Xu, Wei Li, Xiaoyou Zhou, Haoshen Yu, Shuangyang Li, Yunmiao Zhang
Metal materials are prone to serious problems such as material performance degradation, fatigue damage and induced fatigue damage in the process of tension, compression or bearing alternating loads, resulting in heavy losses. Therefore, it is necessary to study the degradation of mechanical properties during material fatigue. When the ultrasonic wave propagates in the metal component, it interacts with the fatigue damage in the material, so that the ultrasonic waveform is distorted and high-order harmonic components are generated, which can be used to characterize the degree of material fatigue and mechanical property degradation. This paper takes YL12 aluminum alloy and 45 steel as the research objects, and uses the COMSOL software to simulate the propagation process of the surface wave in the sample. The specimen is cyclically loaded by a tensile machine, an ultrasonic nonlinear detection platform is built, excitation pulse signal, analyze frequency domain waveform, and the second-order relative nonlinearity of the specimen under different cyclic loading times is calculated. The linear coefficient is obtained, and the relative nonlinear coefficient shows a monotonically increasing trend with the increase of loading times during the fatigue process.
{"title":"Research on Nonlinear Ultrasonic Testing Technology on Fatigue Process of Metal Materials","authors":"Q. Pan, Sa Li, Peilun Li, Lang Xu, Wei Li, Xiaoyou Zhou, Haoshen Yu, Shuangyang Li, Yunmiao Zhang","doi":"10.1109/ICMA54519.2022.9856354","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856354","url":null,"abstract":"Metal materials are prone to serious problems such as material performance degradation, fatigue damage and induced fatigue damage in the process of tension, compression or bearing alternating loads, resulting in heavy losses. Therefore, it is necessary to study the degradation of mechanical properties during material fatigue. When the ultrasonic wave propagates in the metal component, it interacts with the fatigue damage in the material, so that the ultrasonic waveform is distorted and high-order harmonic components are generated, which can be used to characterize the degree of material fatigue and mechanical property degradation. This paper takes YL12 aluminum alloy and 45 steel as the research objects, and uses the COMSOL software to simulate the propagation process of the surface wave in the sample. The specimen is cyclically loaded by a tensile machine, an ultrasonic nonlinear detection platform is built, excitation pulse signal, analyze frequency domain waveform, and the second-order relative nonlinearity of the specimen under different cyclic loading times is calculated. The linear coefficient is obtained, and the relative nonlinear coefficient shows a monotonically increasing trend with the increase of loading times during the fatigue process.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127730507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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