Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter
In order to avoid the increase of input power load caused by the performance degradation of locomotive traction converter capacitor that affects the safe and reliable operation of a traction system, a capacitor fault prediction method is proposed in this paper. Capacitor parameters are identified by...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Control and Information Technology
2021-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.05.017 |
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| _version_ | 1849224814368129024 |
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| author | ZHAN Yanhao YANG Jiawei LU Qingsong |
| author_facet | ZHAN Yanhao YANG Jiawei LU Qingsong |
| author_sort | ZHAN Yanhao |
| collection | DOAJ |
| description | In order to avoid the increase of input power load caused by the performance degradation of locomotive traction converter capacitor that affects the safe and reliable operation of a traction system, a capacitor fault prediction method is proposed in this paper. Capacitor parameters are identified by detecting output voltage ripples of capacitor, and capacitor parameters are fitted based on LS-SVM algorithm to identify the degradation characteristics of capacitor, so as to realize fault prediction of capacitor. Using this method and BP neural network prediction method, taking ESR as capacitance eigenvalue as an example, fault prediction of resonant capacitor and support capacitor in the middle DC circuit of traction converter is carried out. The results show that LS-SVM model has small error, high precision and can better reflect the actual changes. The LS-SVM model is used to pre-warning and verify the on-site operation states and fault situations of the capacitors in recent two years. The results show that the accuracy of this method is higher than 90%, which verifies the effectiveness of the proposed method for capacitor fault prediction. |
| format | Article |
| id | doaj-art-95e6beb158e14af99a62a2fd753473ae |
| institution | Kabale University |
| issn | 2096-5427 |
| language | zho |
| publishDate | 2021-01-01 |
| publisher | Editorial Office of Control and Information Technology |
| record_format | Article |
| series | Kongzhi Yu Xinxi Jishu |
| spelling | doaj-art-95e6beb158e14af99a62a2fd753473ae2025-08-25T06:53:24ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272021-01-013810210782321978Research and Application of Capacitor Fault Prediction forLocomotive Traction ConverterZHAN YanhaoYANG JiaweiLU QingsongIn order to avoid the increase of input power load caused by the performance degradation of locomotive traction converter capacitor that affects the safe and reliable operation of a traction system, a capacitor fault prediction method is proposed in this paper. Capacitor parameters are identified by detecting output voltage ripples of capacitor, and capacitor parameters are fitted based on LS-SVM algorithm to identify the degradation characteristics of capacitor, so as to realize fault prediction of capacitor. Using this method and BP neural network prediction method, taking ESR as capacitance eigenvalue as an example, fault prediction of resonant capacitor and support capacitor in the middle DC circuit of traction converter is carried out. The results show that LS-SVM model has small error, high precision and can better reflect the actual changes. The LS-SVM model is used to pre-warning and verify the on-site operation states and fault situations of the capacitors in recent two years. The results show that the accuracy of this method is higher than 90%, which verifies the effectiveness of the proposed method for capacitor fault prediction.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.05.017traction convertercapacitorparameter identificationLS-SVMfault prediction |
| spellingShingle | ZHAN Yanhao YANG Jiawei LU Qingsong Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter Kongzhi Yu Xinxi Jishu traction converter capacitor parameter identification LS-SVM fault prediction |
| title | Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter |
| title_full | Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter |
| title_fullStr | Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter |
| title_full_unstemmed | Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter |
| title_short | Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter |
| title_sort | research and application of capacitor fault prediction forlocomotive traction converter |
| topic | traction converter capacitor parameter identification LS-SVM fault prediction |
| url | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.05.017 |
| work_keys_str_mv | AT zhanyanhao researchandapplicationofcapacitorfaultpredictionforlocomotivetractionconverter AT yangjiawei researchandapplicationofcapacitorfaultpredictionforlocomotivetractionconverter AT luqingsong researchandapplicationofcapacitorfaultpredictionforlocomotivetractionconverter |