Pub Date : 2024-01-26DOI: 10.1109/ICPECA60615.2024.10471098
Ao Liu, Xin Zhang, Liwei Zhang, Neimeng Yang, Jiachen Song, Yuhang Wang
Starting from the requirements of medium and low speed maglev vehicles for traction system and the design of traction performance, the characteristics of linear motor are determined through size requirements and power analysis. Through the configuration of typical medium and low speed maglev vehicle traction system, the traction system design of medium and low speed maglev train is gradually developed. The traction characteristics, motor size, motor top-level design parameters and motor performance of the motor are analyzed respectively. Based on the demand of traction characteristics, space size and material cost, a linear induction motor suitable for the maglev train of Qingyuan line in Guangdong is designed. Based on this linear motor, the simulation test is carried out. The experiment shows that this design can meet the requirements of medium and low speed maglev traction.
{"title":"Design of Linear Motor for Medium and Low Speed Maglev Train","authors":"Ao Liu, Xin Zhang, Liwei Zhang, Neimeng Yang, Jiachen Song, Yuhang Wang","doi":"10.1109/ICPECA60615.2024.10471098","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471098","url":null,"abstract":"Starting from the requirements of medium and low speed maglev vehicles for traction system and the design of traction performance, the characteristics of linear motor are determined through size requirements and power analysis. Through the configuration of typical medium and low speed maglev vehicle traction system, the traction system design of medium and low speed maglev train is gradually developed. The traction characteristics, motor size, motor top-level design parameters and motor performance of the motor are analyzed respectively. Based on the demand of traction characteristics, space size and material cost, a linear induction motor suitable for the maglev train of Qingyuan line in Guangdong is designed. Based on this linear motor, the simulation test is carried out. The experiment shows that this design can meet the requirements of medium and low speed maglev traction.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"30 4","pages":"576-580"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530308","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 : 2024-01-26DOI: 10.1109/ICPECA60615.2024.10471092
Liu Ya'nan, Xu Gang, Xia Chao, Jianyong Hu, Jianchao Wu
The Synchronous condenser remote diagnosis platform is built under the background of the power Internet of Things technology, with the power grid as the hub, and through data warehouse and data replication technologies to build a data center, achieving the sharing and exchange of information data throughout the company. We apply advanced big data technology to mine operating data and build a reliable, secure, and linearly scalable big data system. With the help of data transformation, outliers can be handled, standardization, generalization, and data aggregation, the inference of fault diagnosis knowledge base will been carried out. Utilizing data warehouse and data mining technology to analyze various indicators in the operation, maintenance and management of the synchronous condenser, we could establish a safety warning evaluation system based on massive data, and combine system operation status estimation technology to ensure the health of the synchronous condenser, achieving precise prediction and coordinated control. Finally, a comparative analysis was conducted between the new system and the traditional status monitoring system, and the superiority of the new system is given.
{"title":"Application of Power Internet of Things Technology in Fault Diagnosis Platform for Synchronous Condenser","authors":"Liu Ya'nan, Xu Gang, Xia Chao, Jianyong Hu, Jianchao Wu","doi":"10.1109/ICPECA60615.2024.10471092","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471092","url":null,"abstract":"The Synchronous condenser remote diagnosis platform is built under the background of the power Internet of Things technology, with the power grid as the hub, and through data warehouse and data replication technologies to build a data center, achieving the sharing and exchange of information data throughout the company. We apply advanced big data technology to mine operating data and build a reliable, secure, and linearly scalable big data system. With the help of data transformation, outliers can be handled, standardization, generalization, and data aggregation, the inference of fault diagnosis knowledge base will been carried out. Utilizing data warehouse and data mining technology to analyze various indicators in the operation, maintenance and management of the synchronous condenser, we could establish a safety warning evaluation system based on massive data, and combine system operation status estimation technology to ensure the health of the synchronous condenser, achieving precise prediction and coordinated control. Finally, a comparative analysis was conducted between the new system and the traditional status monitoring system, and the superiority of the new system is given.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"10 9","pages":"28-32"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530309","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 : 2024-01-26DOI: 10.1109/ICPECA60615.2024.10470961
Xue Tu
To meet the increasing competition in the marketplace during the post epidemic era, it is crucial for the IT industry to swiftly assess and select job seekers while identifying the enhancement skills required for individual job seekers. Current research lacks model optimization and predominantly uses a combination of machine learning methods. However, this study addresses this gap by employing multiple machine learning algorithms based on annual developer survey data from Stack Overflow to predict job seeker skill judgments and quantitative feature scores. The optimized XGBoost model based on the snake optimization algorithm (XGBSO) shows superior performance in accuracy and F1 score compared to other models, accurately predicting the job search ability of programmers. Feature weighting analysis reveals that computer skill is the most crucial feature. The XGBSO model is validated through ROC curves and AUC-ROC values, displaying an accuracy of 0.838 and an F1 score of 0.855, thus indicating excellent performance. The proposed XGBSO model serves as an effective tool for assessing programmers' job search ability and yields significant results.
{"title":"XGBSO: An Employability Assessment Model","authors":"Xue Tu","doi":"10.1109/ICPECA60615.2024.10470961","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10470961","url":null,"abstract":"To meet the increasing competition in the marketplace during the post epidemic era, it is crucial for the IT industry to swiftly assess and select job seekers while identifying the enhancement skills required for individual job seekers. Current research lacks model optimization and predominantly uses a combination of machine learning methods. However, this study addresses this gap by employing multiple machine learning algorithms based on annual developer survey data from Stack Overflow to predict job seeker skill judgments and quantitative feature scores. The optimized XGBoost model based on the snake optimization algorithm (XGBSO) shows superior performance in accuracy and F1 score compared to other models, accurately predicting the job search ability of programmers. Feature weighting analysis reveals that computer skill is the most crucial feature. The XGBSO model is validated through ROC curves and AUC-ROC values, displaying an accuracy of 0.838 and an F1 score of 0.855, thus indicating excellent performance. The proposed XGBSO model serves as an effective tool for assessing programmers' job search ability and yields significant results.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"85 11","pages":"392-397"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530317","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 : 2024-01-26DOI: 10.1109/ICPECA60615.2024.10470990
Junqiang Peng, Zhihao Cai
Aiming at the undesirable characteristics of permanent magnet synchronous linear motor (PMLSM) in the process of movement, such as parameters easy to change, easy to be interfered by sudden load changes, nonlinearity, strong coupling, etc., the fuzzy control idea of variable theory domain is introduced on the premise of the mathematical model of magnetic field oriented permanent magnet synchronous linear motor. This paper constructs the input fuzzy domain expansion factor rule table, uses the fuzzy rules to adjust the expansion factor in real time, changes the fuzzy PID control input fuzzy domain, and realizes the proportional, integral, and differential parameter self-adjustment. The experiments are simulated by MATLAB, and the research results show that the dynamic response speed and robustness of the double fuzzy variable theory domain PID control system are improved compared with the traditional fuzzy PID control and the triple fuzzy variable theory domain PID control.
{"title":"Double Fuzzy PID Control in PMLSM Variable Theory Research","authors":"Junqiang Peng, Zhihao Cai","doi":"10.1109/ICPECA60615.2024.10470990","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10470990","url":null,"abstract":"Aiming at the undesirable characteristics of permanent magnet synchronous linear motor (PMLSM) in the process of movement, such as parameters easy to change, easy to be interfered by sudden load changes, nonlinearity, strong coupling, etc., the fuzzy control idea of variable theory domain is introduced on the premise of the mathematical model of magnetic field oriented permanent magnet synchronous linear motor. This paper constructs the input fuzzy domain expansion factor rule table, uses the fuzzy rules to adjust the expansion factor in real time, changes the fuzzy PID control input fuzzy domain, and realizes the proportional, integral, and differential parameter self-adjustment. The experiments are simulated by MATLAB, and the research results show that the dynamic response speed and robustness of the double fuzzy variable theory domain PID control system are improved compared with the traditional fuzzy PID control and the triple fuzzy variable theory domain PID control.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"83 11","pages":"1005-1010"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530318","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}
For the 300Mva$r$ synchronous condenser, the static frequency converter is used to start it from 0 to 1.05 times of the rated speed for grid connection under pre-determined time. Based on the type test parameters of 300Mvar condenser provided by the manufacturers, losses during startup process is analyzed and converted into resistance torque. The driving torque curve is designed to have different stages of the startup process for best control of the process. A method is put forward to calculate the SFC capacity so that the startup time of 300Mvar synchronous condenser shall satisfy the requirement and the correctness of SFC capacity calculation method is verified by engineering projects.
{"title":"Capacity Calculation of Static Frequency Converter for 300Mvar Synchronous Condenser","authors":"Yin Zhang, Yazhou Yuan, Ruiqi Zhang, Qiang Wu, Lingfeng Sun, Wenqian Ji, Hongchao Zhu, Shaoxing Zhao","doi":"10.1109/ICPECA60615.2024.10471183","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471183","url":null,"abstract":"For the 300Mva$r$ synchronous condenser, the static frequency converter is used to start it from 0 to 1.05 times of the rated speed for grid connection under pre-determined time. Based on the type test parameters of 300Mvar condenser provided by the manufacturers, losses during startup process is analyzed and converted into resistance torque. The driving torque curve is designed to have different stages of the startup process for best control of the process. A method is put forward to calculate the SFC capacity so that the startup time of 300Mvar synchronous condenser shall satisfy the requirement and the correctness of SFC capacity calculation method is verified by engineering projects.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"14 4","pages":"464-467"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530133","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}
In recent years, current control strategy has played an important role in power system stability analysis. Based on the doubly-fed wind turbine model, the effects of PI- R, PI, IP and adaptive control strategies on the dynamic performance of the system are analyzed and compared. In this paper, the mathematical model of the doubly-fed induction generator is established in the rotating d-q axis frame, and the transfer function of the current controller is deduced and analyzed. On this basis, four current control strategy models are established. The simulation results show that all the control systems have strong robustness when the parameters are uncertain. Moreover, compared with other control strategies, PI-R has better dynamic performance. This method can solve the control problem of wind power system based on DFIG under unbalanced loads and nonlinear loads.
{"title":"Study on Current Controller of Doubly-Fed Induction Generator with Variable Parameters","authors":"Maimaitireyimu Abulizi, Wenjie Shi, Yangteng Hu, Maidina Bahati, Chao Zhang","doi":"10.1109/ICPECA60615.2024.10471129","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471129","url":null,"abstract":"In recent years, current control strategy has played an important role in power system stability analysis. Based on the doubly-fed wind turbine model, the effects of PI- R, PI, IP and adaptive control strategies on the dynamic performance of the system are analyzed and compared. In this paper, the mathematical model of the doubly-fed induction generator is established in the rotating d-q axis frame, and the transfer function of the current controller is deduced and analyzed. On this basis, four current control strategy models are established. The simulation results show that all the control systems have strong robustness when the parameters are uncertain. Moreover, compared with other control strategies, PI-R has better dynamic performance. This method can solve the control problem of wind power system based on DFIG under unbalanced loads and nonlinear loads.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"65 3","pages":"484-489"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530477","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 : 2024-01-26DOI: 10.1109/ICPECA60615.2024.10471155
Ningping Tang, Bo Gao
With the continuous development of power systems and the deepening of power safety supervision work, it is particularly important to effectively identify and monitor the behavior of power safety supervision personnel. This research aims to improve the accuracy and real-time performance of personnel behavior recognition in the field of electric power safety supervision through advanced neural network technology. First, this study conducts an in-depth analysis of the common behaviors of electric power safety supervisors, including daily inspections, accident handling, equipment maintenance and other tasks. On this basis, a behavior recognition model based on neural network algorithm is proposed. This model combines deep learning and pattern recognition methods and can accurately classify various behaviors of power safety supervisors. Secondly, a large amount of field data was used for training and testing in the study to ensure the robustness and generalization ability of the model. Furthermore, this study focuses on the real-time and adaptability of the algorithm. Taking into account the particularity of power safety supervision, by adjusting the structure and parameters of the neural network, the algorithm can perform behavior recognition more efficiently in real-time scenarios, and the training of neural networks optimizes the performance of the algorithm. Experiments have proven that the proposed behavior recognition model based on neural network algorithm has high accuracy and robustness in classifying human behavior.
{"title":"Research on the Robustness of Behavior Recognition Model in Power Safety Monitoring Based on Neural Network Algorithm","authors":"Ningping Tang, Bo Gao","doi":"10.1109/ICPECA60615.2024.10471155","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471155","url":null,"abstract":"With the continuous development of power systems and the deepening of power safety supervision work, it is particularly important to effectively identify and monitor the behavior of power safety supervision personnel. This research aims to improve the accuracy and real-time performance of personnel behavior recognition in the field of electric power safety supervision through advanced neural network technology. First, this study conducts an in-depth analysis of the common behaviors of electric power safety supervisors, including daily inspections, accident handling, equipment maintenance and other tasks. On this basis, a behavior recognition model based on neural network algorithm is proposed. This model combines deep learning and pattern recognition methods and can accurately classify various behaviors of power safety supervisors. Secondly, a large amount of field data was used for training and testing in the study to ensure the robustness and generalization ability of the model. Furthermore, this study focuses on the real-time and adaptability of the algorithm. Taking into account the particularity of power safety supervision, by adjusting the structure and parameters of the neural network, the algorithm can perform behavior recognition more efficiently in real-time scenarios, and the training of neural networks optimizes the performance of the algorithm. Experiments have proven that the proposed behavior recognition model based on neural network algorithm has high accuracy and robustness in classifying human behavior.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"86 2","pages":"995-999"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530372","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 : 2024-01-26DOI: 10.1109/ICPECA60615.2024.10471104
Suqin Xiong, Yang Li, Qiuyang Li, Jianning Guo
This paper designs a DC charging station measurement and monitoring system for electric vehicles based on DC metering chips, integrating DC meters and billing control units, and integrating DC meters, splitters, and billing control units. Implementing an integrated design approach, the system comprises a Metering Module and a Billing Control Module. The Metering Module is tasked with gathering and quantifying the charger's energy consumption. It transmits the recorded voltage, current, and energy data to the Billing Control Module. The Billing Control Module, in turn, engages with users and performs various functions including fee payment, charging mode selection, and control of the charging device.
{"title":"Design and Research of a DC Charging Station Measurement and Monitoring System for Electric Vehicles Based on DC Measurement Chips","authors":"Suqin Xiong, Yang Li, Qiuyang Li, Jianning Guo","doi":"10.1109/ICPECA60615.2024.10471104","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471104","url":null,"abstract":"This paper designs a DC charging station measurement and monitoring system for electric vehicles based on DC metering chips, integrating DC meters and billing control units, and integrating DC meters, splitters, and billing control units. Implementing an integrated design approach, the system comprises a Metering Module and a Billing Control Module. The Metering Module is tasked with gathering and quantifying the charger's energy consumption. It transmits the recorded voltage, current, and energy data to the Billing Control Module. The Billing Control Module, in turn, engages with users and performs various functions including fee payment, charging mode selection, and control of the charging device.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"27 4","pages":"1344-1347"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530507","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 : 2024-01-26DOI: 10.1109/ICPECA60615.2024.10471025
Ruijiang Zeng, Shu Huang
As the key equipment of the intelligent electric power distribution room, the electric power distribution gateway is the main equipment to realize the distribution IoT. In order to ensure its normal operation, regular operation and maintenance are required. At present, the research on the operation and maintenance technology of the intelligent electric power distribution room mostly focuses on the detection of the communication protocol of the intelligent terminal and the design of the operation and maintenance master station platform, while the research on the on-site operation and maintenance tools of the electric power distribution gateway is difficult to find. Therefore, this paper studies this technology. First, based on the architecture of “cloud management edge and end” of the electric power distribution IoT, the automatic closed-loop test architecture of cloud edge collaboration is designed, and the cloud edge collaboration function of the portable operation and maintenance test tool is defined. Secondly, the software and hardware design as well as the portable design of the on-site portable operation and maintenance testing tools were elaborated, ensuring the lightweight and portable operation and maintenance tool while ensuring the cloud edge collaborative operation and maintenance testing function. Finally, the feasibility of the technology is verified by field application, and the intelligent operation and maintenance level of the electric power distribution gateway is greatly improved.
{"title":"Design and application of a portable electric power distribution gateway operation and maintenance test tool based on cloud edge collaboration","authors":"Ruijiang Zeng, Shu Huang","doi":"10.1109/ICPECA60615.2024.10471025","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471025","url":null,"abstract":"As the key equipment of the intelligent electric power distribution room, the electric power distribution gateway is the main equipment to realize the distribution IoT. In order to ensure its normal operation, regular operation and maintenance are required. At present, the research on the operation and maintenance technology of the intelligent electric power distribution room mostly focuses on the detection of the communication protocol of the intelligent terminal and the design of the operation and maintenance master station platform, while the research on the on-site operation and maintenance tools of the electric power distribution gateway is difficult to find. Therefore, this paper studies this technology. First, based on the architecture of “cloud management edge and end” of the electric power distribution IoT, the automatic closed-loop test architecture of cloud edge collaboration is designed, and the cloud edge collaboration function of the portable operation and maintenance test tool is defined. Secondly, the software and hardware design as well as the portable design of the on-site portable operation and maintenance testing tools were elaborated, ensuring the lightweight and portable operation and maintenance tool while ensuring the cloud edge collaborative operation and maintenance testing function. Finally, the feasibility of the technology is verified by field application, and the intelligent operation and maintenance level of the electric power distribution gateway is greatly improved.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"87 5","pages":"267-274"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530315","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 : 2024-01-26DOI: 10.1109/ICPECA60615.2024.10470999
Hongbin Yu, Shuangyang Yang
Aiming at the problem that the accuracy of the attitude monitoring system of the aircraft horizontal attitude is not high in the process of aircraft jacking, and some staff need to determine whether the aircraft is level through the trim indicator. Therefore, an attitude calculation method based on improved complementary filtering and EKF/KF fusion was proposed. In this method, the data of gyroscope and accelerometer are fused by complementary filtering and PID algorithm, and the obtained attitude data and the output data of the accelerometer are fused by extended Kalman filter. Finally, the heading Angle in the obtained attitude Angle is fused with the magnetometer data by linear Kalman filter to obtain the final attitude. The optimal attitude estimation of the aircraft jacking process is completed.
{"title":"Research on Attitude Resolution Method Based on Improved Complementary Filtering","authors":"Hongbin Yu, Shuangyang Yang","doi":"10.1109/ICPECA60615.2024.10470999","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10470999","url":null,"abstract":"Aiming at the problem that the accuracy of the attitude monitoring system of the aircraft horizontal attitude is not high in the process of aircraft jacking, and some staff need to determine whether the aircraft is level through the trim indicator. Therefore, an attitude calculation method based on improved complementary filtering and EKF/KF fusion was proposed. In this method, the data of gyroscope and accelerometer are fused by complementary filtering and PID algorithm, and the obtained attitude data and the output data of the accelerometer are fused by extended Kalman filter. Finally, the heading Angle in the obtained attitude Angle is fused with the magnetometer data by linear Kalman filter to obtain the final attitude. The optimal attitude estimation of the aircraft jacking process is completed.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"110 2","pages":"1096-1101"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530466","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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