Pub Date : 2022-12-16DOI: 10.1109/ICIEA54703.2022.10006235
Yuansong Cai, Shiqian Wu
Simultaneous Localization and Mapping(SLAM) has broad applications such as driverless cars and indoor service robots. The SLAM techniques usually assume that environments are static, and it is difficult to obtain good accuracy in highly dynamic scenes. In this paper, we adopt the semantic segmentation method to filter out dynamic points according to prior knowledge. To avoid tracking failure due to insufficient feature points, epipolar geometry is used to retain potential dynamic points as much as possible. The proposed method is implemented based on the classical SLAM framework ORBSLAM2 and carried out experiments on the TUM RGBD datasets. Compared with ORBSLAM2, the localization accuracy of this algorithm is improved by 95% in highly dynamic environments.
{"title":"A Robust SLAM For Highly Dynamic Environments","authors":"Yuansong Cai, Shiqian Wu","doi":"10.1109/ICIEA54703.2022.10006235","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10006235","url":null,"abstract":"Simultaneous Localization and Mapping(SLAM) has broad applications such as driverless cars and indoor service robots. The SLAM techniques usually assume that environments are static, and it is difficult to obtain good accuracy in highly dynamic scenes. In this paper, we adopt the semantic segmentation method to filter out dynamic points according to prior knowledge. To avoid tracking failure due to insufficient feature points, epipolar geometry is used to retain potential dynamic points as much as possible. The proposed method is implemented based on the classical SLAM framework ORBSLAM2 and carried out experiments on the TUM RGBD datasets. Compared with ORBSLAM2, the localization accuracy of this algorithm is improved by 95% in highly dynamic environments.","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115133450","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}
Multilevel DC-DC converters have many advantages over traditional two-level DC-DC converters, such as decreasing voltage stress of switches, reducing inductor volume and switching losses. To apply multilevel topologies, some measures must be considered to deal with the risk of the capacitor voltage unbalanced. The traditional voltage balance scheme requires a large number of sensors to measure the voltage of each capacitor, which is not conducive to low cost and small volume. To solve this problem, this paper proposes a balancing control method based on decoupling single voltage sensor signal for five-level buck/boost converter. The proposed control method can balance the voltage of the divided capacitors through adjusting the duty cycle of the power switches. And the working principle is introduced in detail, and the decoupling algorithm is derived and analyzed. Finally, the simulation results verify that control method with single voltage sensor is feasible to balance all capacitor voltages.
{"title":"A Balancing Control Method with Single voltage Sensor for Five-Level Buck/Boost Converter","authors":"Muyang Liu, Zhigang Yao, Xinyu He, Linlong Jiang, Wei-rong Chen","doi":"10.1109/ICIEA54703.2022.10006172","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10006172","url":null,"abstract":"Multilevel DC-DC converters have many advantages over traditional two-level DC-DC converters, such as decreasing voltage stress of switches, reducing inductor volume and switching losses. To apply multilevel topologies, some measures must be considered to deal with the risk of the capacitor voltage unbalanced. The traditional voltage balance scheme requires a large number of sensors to measure the voltage of each capacitor, which is not conducive to low cost and small volume. To solve this problem, this paper proposes a balancing control method based on decoupling single voltage sensor signal for five-level buck/boost converter. The proposed control method can balance the voltage of the divided capacitors through adjusting the duty cycle of the power switches. And the working principle is introduced in detail, and the decoupling algorithm is derived and analyzed. Finally, the simulation results verify that control method with single voltage sensor is feasible to balance all capacitor voltages.","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115606971","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 : 2022-12-16DOI: 10.1109/ICIEA54703.2022.10006179
J. An, Jin Xiao, Xiaoguang Hu, Qing Zhou
Military radar is often used to collect information of battlefield situation, detect targets and guide weapon systems to lock them. Electronic warfare is a counter-measure against enemy radar. In this paper, the co-simulation method of Systems Tool Kit (STK) and MATLAB is proposed to simulate the detection range of enemy radar suppressed by the jammer in three-dimensional electronic warfare environment. Firstly, Radar detection range models on 2D and 3D are established respectively by combining horizontal and vertical direction functions with basic radar equations. Secondly, radar detection range variation under selfscreening jamming (SSJ) of one aircraft is studied. Then, the leader-follower algorithm is used to realize escort jamming (ESJ) model under multi-aircraft formation. Finally, the radar detection range of multiple aircraft jamming is compared with the range of a single aircraft jamming. The 3D radar detection range simulation results in STK vividly show that adopting multiaircraft jamming can greatly reduce the detection range of enemy radar and successfully strike the enemy.
{"title":"A New Co-simulation Method of Radar Detection Range under Suppression Jamming","authors":"J. An, Jin Xiao, Xiaoguang Hu, Qing Zhou","doi":"10.1109/ICIEA54703.2022.10006179","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10006179","url":null,"abstract":"Military radar is often used to collect information of battlefield situation, detect targets and guide weapon systems to lock them. Electronic warfare is a counter-measure against enemy radar. In this paper, the co-simulation method of Systems Tool Kit (STK) and MATLAB is proposed to simulate the detection range of enemy radar suppressed by the jammer in three-dimensional electronic warfare environment. Firstly, Radar detection range models on 2D and 3D are established respectively by combining horizontal and vertical direction functions with basic radar equations. Secondly, radar detection range variation under selfscreening jamming (SSJ) of one aircraft is studied. Then, the leader-follower algorithm is used to realize escort jamming (ESJ) model under multi-aircraft formation. Finally, the radar detection range of multiple aircraft jamming is compared with the range of a single aircraft jamming. The 3D radar detection range simulation results in STK vividly show that adopting multiaircraft jamming can greatly reduce the detection range of enemy radar and successfully strike the enemy.","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116846050","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 : 2022-12-16DOI: 10.1109/ICIEA54703.2022.10006146
Shangzhu Jin, Run Xue, Jun Peng, Yan Zhao, JieRui Yin
Aiming at the problem that depression has become severe social problems and most of patients can not be diagnosed early. As social media has become popular in the world like Chinese microblogs and twitters, a large amount of data can be used for the researches, especially the contents published originally can be used to detect whether publisher is depressed. However, depression prediction is not the same as text classification, it is difficult to find a unified standard to determine depression. In this regard, a method combining machine learning and TF-IDF is proposed. The method treats micro-blog contents as a whole to generate features to predict whether the micro-blog users get depressed. The experiment shows that the proposed method can effectively identify potential depressive patients among micro-blog users.
{"title":"Combing TF-IDF with machine learning to detect depression in Microblog","authors":"Shangzhu Jin, Run Xue, Jun Peng, Yan Zhao, JieRui Yin","doi":"10.1109/ICIEA54703.2022.10006146","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10006146","url":null,"abstract":"Aiming at the problem that depression has become severe social problems and most of patients can not be diagnosed early. As social media has become popular in the world like Chinese microblogs and twitters, a large amount of data can be used for the researches, especially the contents published originally can be used to detect whether publisher is depressed. However, depression prediction is not the same as text classification, it is difficult to find a unified standard to determine depression. In this regard, a method combining machine learning and TF-IDF is proposed. The method treats micro-blog contents as a whole to generate features to predict whether the micro-blog users get depressed. The experiment shows that the proposed method can effectively identify potential depressive patients among micro-blog users.","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125815399","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 : 2022-12-16DOI: 10.1109/ICIEA54703.2022.10006026
Cun Hu, Kai Wang, Jicheng Cai, Yue Zhang, Zilin Liang, Weihai Chen
This In the experiment of brain-computer interface motor imagery, CSP is often used for feature extraction. CSP is a supervised learning algorithm that requires a large amount of sample data for training. However, the EEG signal is non- stationary, and the fixed CSP spatial filter does not have an ideal classification effect when there are few training samples. To solve this problem, this paper proposes an adaptive co-space mode. It can continuously update the spatial filter according to the data changes, and then perform feature extraction. This paper takes the data of the third brain-computer interface competition Iva as the processing object. Considering the influence of different EEG regions on classification, we have selected 4 different regions to compare and explore the classification accuracy of CSP and ACSP respectively. In the results, the average classification accuracy of CSP and ACSP is higher than that of CSP in four areas. It shows that the classification performance of ACSP is better than that of traditional CSP
{"title":"An Adaptive Common Spatial Pattern for EEG Signal Classification in Different Channel","authors":"Cun Hu, Kai Wang, Jicheng Cai, Yue Zhang, Zilin Liang, Weihai Chen","doi":"10.1109/ICIEA54703.2022.10006026","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10006026","url":null,"abstract":"This In the experiment of brain-computer interface motor imagery, CSP is often used for feature extraction. CSP is a supervised learning algorithm that requires a large amount of sample data for training. However, the EEG signal is non- stationary, and the fixed CSP spatial filter does not have an ideal classification effect when there are few training samples. To solve this problem, this paper proposes an adaptive co-space mode. It can continuously update the spatial filter according to the data changes, and then perform feature extraction. This paper takes the data of the third brain-computer interface competition Iva as the processing object. Considering the influence of different EEG regions on classification, we have selected 4 different regions to compare and explore the classification accuracy of CSP and ACSP respectively. In the results, the average classification accuracy of CSP and ACSP is higher than that of CSP in four areas. It shows that the classification performance of ACSP is better than that of traditional CSP","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122653353","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 : 2022-12-16DOI: 10.1109/ICIEA54703.2022.10006232
T. Lan, Yan Zhang, Wanhong Zhang
When the quasi-Z-source inverter with energy storage (ES-qZSI) by model predictive control (MPC), an appropriate weighting factor is designed in the cost function to achieve the best possible performance from the system. However, adding weighting factors directly to a cost function produces both numerical instability and computational complexity, in addition to the inability to distinguish between the role of weighting factors and system dynamics in the performance of the relevant system. This paper proposes an improved MPC algorithm without weighting factors for the ES-qZSI system. The computational cost of MPC is significantly reduced by the voltage vector control method without affecting the control performance. Moreover, the inductance current term in the control logic is considered individually, thus eliminating its weighting factor. Compared with conventional MPC, computational efficiency and control performance are demonstrated via numerical simulation. The simulation results show a good dynamic and static performance for the improved algorithm.
{"title":"Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor","authors":"T. Lan, Yan Zhang, Wanhong Zhang","doi":"10.1109/ICIEA54703.2022.10006232","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10006232","url":null,"abstract":"When the quasi-Z-source inverter with energy storage (ES-qZSI) by model predictive control (MPC), an appropriate weighting factor is designed in the cost function to achieve the best possible performance from the system. However, adding weighting factors directly to a cost function produces both numerical instability and computational complexity, in addition to the inability to distinguish between the role of weighting factors and system dynamics in the performance of the relevant system. This paper proposes an improved MPC algorithm without weighting factors for the ES-qZSI system. The computational cost of MPC is significantly reduced by the voltage vector control method without affecting the control performance. Moreover, the inductance current term in the control logic is considered individually, thus eliminating its weighting factor. Compared with conventional MPC, computational efficiency and control performance are demonstrated via numerical simulation. The simulation results show a good dynamic and static performance for the improved algorithm.","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122042391","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 : 2022-12-16DOI: 10.1109/ICIEA54703.2022.10006101
Yixiong Tang, Jiaming Zhang, Wenjun Xu, Jiayi Liu, Zhenrui Ji, Yang Hu
The development of digital twin (DT) promotes the digitalization of manufacturing process, which makes the connection between physical equipment and digital equipment closer, and the DT model has the characteristics of dynamic, accurate and real-time. Whether from the perspective of the architecture of DT technology or the construction of DT model, the consistency of DT model is an important standard to evaluate the accuracy of it. Based on the physical model of the DT model of typical robotic pick-and-place process, this paper proposes a consistency analysis method. Considering the complexity of the physical model, the paper takes the dynamics model as its main part, and a DT model based on pick-and-place process is constructed using the ABB IRB1200 industrial robot. Finally, taking a typical robotic pick-and-place process as the scenario, a case study is carried out to verify the consistency analysis method for the physical model of DT model of this process under the conditions of simple friction model and modified friction model. The experimental results show that the consistency of the physical model of the DT model of pick-and-place process established in this paper can satisfy the requirements within the acceptable range and the use of modified friction model is helpful to improve its consistency.
{"title":"Consistency Analysis of Digital Twin Model used for Typical Robotic Pick-and-Place Process","authors":"Yixiong Tang, Jiaming Zhang, Wenjun Xu, Jiayi Liu, Zhenrui Ji, Yang Hu","doi":"10.1109/ICIEA54703.2022.10006101","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10006101","url":null,"abstract":"The development of digital twin (DT) promotes the digitalization of manufacturing process, which makes the connection between physical equipment and digital equipment closer, and the DT model has the characteristics of dynamic, accurate and real-time. Whether from the perspective of the architecture of DT technology or the construction of DT model, the consistency of DT model is an important standard to evaluate the accuracy of it. Based on the physical model of the DT model of typical robotic pick-and-place process, this paper proposes a consistency analysis method. Considering the complexity of the physical model, the paper takes the dynamics model as its main part, and a DT model based on pick-and-place process is constructed using the ABB IRB1200 industrial robot. Finally, taking a typical robotic pick-and-place process as the scenario, a case study is carried out to verify the consistency analysis method for the physical model of DT model of this process under the conditions of simple friction model and modified friction model. The experimental results show that the consistency of the physical model of the DT model of pick-and-place process established in this paper can satisfy the requirements within the acceptable range and the use of modified friction model is helpful to improve its consistency.","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128536874","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}
Active front end (AFE) acts as the interface of energy conversion for renewable energy generation systems and gradually becomes more and more prominent. For controlling AFE, finite-control-set model predictive control (FCS-MPC) has been considered a promising alternative. However, owing to its high dependence on system models, system parameter variations (in particular, the grid-side inductance) and external disturbance will seriously result in degradation of its control performance and even instability. Therefore, in this work, a data-driven predictive control (DDPC) method with a neural network (NN) is proposed and validated for an AFE. Based on the existing NN predictor, the proposed solution not only covers the robustness of state variables against parameter variations, but also takes the input variables into account, which further enhances the system robustness. Control performances of the proposed method are validated and compared with the classical FCS-MPC scheme through both simulation and experimental results.
主动前端(Active front end, AFE)作为可再生能源发电系统能量转换的接口，逐渐凸显出来。对于AFE的控制，有限控制集模型预测控制(FCS-MPC)被认为是一种很有前途的替代方法。然而，由于其对系统模型的高度依赖，系统参数的变化(特别是网侧电感)和外部干扰将严重导致其控制性能下降甚至不稳定。因此，本文提出了一种基于神经网络的数据驱动预测控制(DDPC)方法，并对其进行了验证。在已有的神经网络预测器的基础上，该方法不仅涵盖了状态变量对参数变化的鲁棒性，而且考虑了输入变量，进一步增强了系统的鲁棒性。通过仿真和实验结果，验证了该方法的控制性能，并与经典的FCS-MPC方案进行了比较。
{"title":"Data-Driven Predictive Current Control for Active Front Ends with Neural Networks","authors":"Haoyu Chen, Zhenbin Zhang, Zhen Li, Pinjia Zhang, Mingyuan Zhang","doi":"10.1109/ICIEA54703.2022.10006029","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10006029","url":null,"abstract":"Active front end (AFE) acts as the interface of energy conversion for renewable energy generation systems and gradually becomes more and more prominent. For controlling AFE, finite-control-set model predictive control (FCS-MPC) has been considered a promising alternative. However, owing to its high dependence on system models, system parameter variations (in particular, the grid-side inductance) and external disturbance will seriously result in degradation of its control performance and even instability. Therefore, in this work, a data-driven predictive control (DDPC) method with a neural network (NN) is proposed and validated for an AFE. Based on the existing NN predictor, the proposed solution not only covers the robustness of state variables against parameter variations, but also takes the input variables into account, which further enhances the system robustness. Control performances of the proposed method are validated and compared with the classical FCS-MPC scheme through both simulation and experimental results.","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129252245","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 : 2022-12-16DOI: 10.1109/ICIEA54703.2022.10005975
A. Diab, A. Aboelhassan, Shuo Wang, Feng Guo, S. Yeoh, S. Bozhko, M. Rashed, M. Galea
Discrete synchronous reference frame proportional integral Current Controller (CC) delivers superior control performance for high-speed drives due to its ability to accurately compensate for cross-coupling terms. Complete compensation can only be achieved if the machine parameters and operating conditions do not change considerably during operation, however, this is not the case for many aircraft applications. For example, aircraft electrical starter-generator system operating frequencies can change significantly due to the engine’s large speed range. This paper therefore thoroughly investigates the dynamic performance of the discrete CC considering a wide variation of the machine parameters and operating frequencies which has not been addressed in the literature. A multivariable discrete-time domain model of the current control system is proposed for the assessment of the dynamic performances under different operating conditions. The addition of an active damping element has also been considered to improve the disturbance rejection capability of the complex vector decoupling approach. The key paper findings have been successfully confirmed by comprehensive time-domain simulations.
{"title":"Performance Analysis of Complex Vector Discrete Current Controller for High-Speed Permanent Magnet Machines","authors":"A. Diab, A. Aboelhassan, Shuo Wang, Feng Guo, S. Yeoh, S. Bozhko, M. Rashed, M. Galea","doi":"10.1109/ICIEA54703.2022.10005975","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10005975","url":null,"abstract":"Discrete synchronous reference frame proportional integral Current Controller (CC) delivers superior control performance for high-speed drives due to its ability to accurately compensate for cross-coupling terms. Complete compensation can only be achieved if the machine parameters and operating conditions do not change considerably during operation, however, this is not the case for many aircraft applications. For example, aircraft electrical starter-generator system operating frequencies can change significantly due to the engine’s large speed range. This paper therefore thoroughly investigates the dynamic performance of the discrete CC considering a wide variation of the machine parameters and operating frequencies which has not been addressed in the literature. A multivariable discrete-time domain model of the current control system is proposed for the assessment of the dynamic performances under different operating conditions. The addition of an active damping element has also been considered to improve the disturbance rejection capability of the complex vector decoupling approach. The key paper findings have been successfully confirmed by comprehensive time-domain simulations.","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124614888","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 : 2022-12-16DOI: 10.1109/ICIEA54703.2022.10006315
R. Liu, Liang Dong, Jianqiao Yang, Yinchi Tang
The electromagnetic vibration and noise level of the asynchronous motor affects the performance and life of the motor. In order to study the causes of electromagnetic vibration and noise. This paper takes a four-pole squirrel-cage asynchronous motor as the research object, establishes an asynchronous motor's magnetic-solid-acoustic multi-physics simulation model, analyzes the distribution characteristics of electromagnetic vibration and noise. The electromagnetic noise of the asynchronous motor is mainly generated by the radial electromagnetic force on the stator teeth. By adjusting the stator slot bottom width, the air gap magnetic density can be changed, so as to optimize the radial electromagnetic force and achieve the effect of weakening the electromagnetic vibration and noise of the motor. First, the air gap magnetic density between the stator and the rotor is analyzed by the combination of numerical analysis and finite element method. The Maxwell stress tensor method is used to calculate the radial electromagnetic force, which is consistent with the results obtained by the finite element simulation. The time and space character of the radial electromagnetic force are obtained through spectrum analysis, and then the order and frequency of the radial electromagnetic force are obtained. Combined with harmonic response analysis and acoustic radiation theory, the vibration and noise results of the squirrel-cage asynchronous motor are obtained. Finally, by analyzing the electromagnetic vibration and noise results of asynchronous motors under different stator slot bottom widths, the study found when the slot bottom width is 12.4mm, a lower level of the electromagnetic noise can be obtained.
{"title":"Influence of Stator Slot Bottom Width on Electromagnetic Vibration and Noise of Asynchronous Motor","authors":"R. Liu, Liang Dong, Jianqiao Yang, Yinchi Tang","doi":"10.1109/ICIEA54703.2022.10006315","DOIUrl":"https://doi.org/10.1109/ICIEA54703.2022.10006315","url":null,"abstract":"The electromagnetic vibration and noise level of the asynchronous motor affects the performance and life of the motor. In order to study the causes of electromagnetic vibration and noise. This paper takes a four-pole squirrel-cage asynchronous motor as the research object, establishes an asynchronous motor's magnetic-solid-acoustic multi-physics simulation model, analyzes the distribution characteristics of electromagnetic vibration and noise. The electromagnetic noise of the asynchronous motor is mainly generated by the radial electromagnetic force on the stator teeth. By adjusting the stator slot bottom width, the air gap magnetic density can be changed, so as to optimize the radial electromagnetic force and achieve the effect of weakening the electromagnetic vibration and noise of the motor. First, the air gap magnetic density between the stator and the rotor is analyzed by the combination of numerical analysis and finite element method. The Maxwell stress tensor method is used to calculate the radial electromagnetic force, which is consistent with the results obtained by the finite element simulation. The time and space character of the radial electromagnetic force are obtained through spectrum analysis, and then the order and frequency of the radial electromagnetic force are obtained. Combined with harmonic response analysis and acoustic radiation theory, the vibration and noise results of the squirrel-cage asynchronous motor are obtained. Finally, by analyzing the electromagnetic vibration and noise results of asynchronous motors under different stator slot bottom widths, the study found when the slot bottom width is 12.4mm, a lower level of the electromagnetic noise can be obtained.","PeriodicalId":448444,"journal":{"name":"2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129872811","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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