Research on State Diagnosis Methods of UHF Partial Discharge Sensors Based on Improved ViT
UHF partial discharge sensors are key equipment for substation monitoring, but they are subject to complex multi-physical field stresses in substation applications, which leads to a significantly higher failure rate among UHF partial discharge sensors used in substations compared to other applicatio...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/23/11214 |
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| author | Yingyi Liu Zhenghao Hu Lin Cheng Yan Wang Chuan Chen |
| author_facet | Yingyi Liu Zhenghao Hu Lin Cheng Yan Wang Chuan Chen |
| author_sort | Yingyi Liu |
| collection | DOAJ |
| description | UHF partial discharge sensors are key equipment for substation monitoring, but they are subject to complex multi-physical field stresses in substation applications, which leads to a significantly higher failure rate among UHF partial discharge sensors used in substations compared to other applications. Effective fault diagnosis is of great significance for improving the safety of substations. In this paper, we propose an improved model based on ViT (Vision Transformer), which effectively identifies the local features of the data by designing a sliding window mechanism, and has a good feature extraction capability for the feature library formed by UHF partial discharge sensors. The experimental results show that the diagnostic accuracy of the improved model, based on the ViT model, can reach 97.6%, which can effectively improve classification accuracy and shorten training times compared with the ViT model. |
| format | Article |
| id | doaj-art-25b00e5af1f744928a9f4beaad29fa84 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-25b00e5af1f744928a9f4beaad29fa842025-08-20T01:55:28ZengMDPI AGApplied Sciences2076-34172024-12-0114231121410.3390/app142311214Research on State Diagnosis Methods of UHF Partial Discharge Sensors Based on Improved ViTYingyi Liu0Zhenghao Hu1Lin Cheng2Yan Wang3Chuan Chen4School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, ChinaSchool of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, ChinaState Grid Shaanxi Electric Power Co., Ltd., Xi’an 710048, ChinaState Grid Corporation of China, National Smart Grid Research Institute Co., Ltd., Beijing 102209, ChinaState Grid Corporation of China, National Smart Grid Research Institute Co., Ltd., Beijing 102209, ChinaUHF partial discharge sensors are key equipment for substation monitoring, but they are subject to complex multi-physical field stresses in substation applications, which leads to a significantly higher failure rate among UHF partial discharge sensors used in substations compared to other applications. Effective fault diagnosis is of great significance for improving the safety of substations. In this paper, we propose an improved model based on ViT (Vision Transformer), which effectively identifies the local features of the data by designing a sliding window mechanism, and has a good feature extraction capability for the feature library formed by UHF partial discharge sensors. The experimental results show that the diagnostic accuracy of the improved model, based on the ViT model, can reach 97.6%, which can effectively improve classification accuracy and shorten training times compared with the ViT model.https://www.mdpi.com/2076-3417/14/23/11214UHF partial discharge sensorstate diagnosisdeep learningvision transformer |
| spellingShingle | Yingyi Liu Zhenghao Hu Lin Cheng Yan Wang Chuan Chen Research on State Diagnosis Methods of UHF Partial Discharge Sensors Based on Improved ViT Applied Sciences UHF partial discharge sensor state diagnosis deep learning vision transformer |
| title | Research on State Diagnosis Methods of UHF Partial Discharge Sensors Based on Improved ViT |
| title_full | Research on State Diagnosis Methods of UHF Partial Discharge Sensors Based on Improved ViT |
| title_fullStr | Research on State Diagnosis Methods of UHF Partial Discharge Sensors Based on Improved ViT |
| title_full_unstemmed | Research on State Diagnosis Methods of UHF Partial Discharge Sensors Based on Improved ViT |
| title_short | Research on State Diagnosis Methods of UHF Partial Discharge Sensors Based on Improved ViT |
| title_sort | research on state diagnosis methods of uhf partial discharge sensors based on improved vit |
| topic | UHF partial discharge sensor state diagnosis deep learning vision transformer |
| url | https://www.mdpi.com/2076-3417/14/23/11214 |
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