Acoustic Multi-Parameter Early Warning Method for Transformer DC Bias State
The acoustic signal in the operation of a power transformer contains a lot of transformer operation state information, which is of great significance to the detection of DC bias state. In this paper, three typical parameters used for DC bias state detection are selected by comparing the acoustic var...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/8/2906 |
| _version_ | 1797434250115416064 |
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| author | Yuhao Zhou Bowen Wang |
| author_facet | Yuhao Zhou Bowen Wang |
| author_sort | Yuhao Zhou |
| collection | DOAJ |
| description | The acoustic signal in the operation of a power transformer contains a lot of transformer operation state information, which is of great significance to the detection of DC bias state. In this paper, three typical parameters used for DC bias state detection are selected by comparing the acoustic variation of a 500 kV Jingting transformer substation No. 2 transformer with that of the core model built in the laboratory; then, acoustic samples of the 162 EHV normal state transformers are collected, and the distribution regularity of three typical parameters in normal state is given. Finally, according to the distribution regularity, clear warning threshold of typical parameters are given, and the DC bias cases from the 500 kV Jingting transformer substation are used to verify the effectiveness of the threshold. |
| first_indexed | 2024-03-09T10:30:30Z |
| format | Article |
| id | doaj.art-d1b01ae9e5d542ee8c1eb74899a5d555 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T10:30:30Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d1b01ae9e5d542ee8c1eb74899a5d5552023-12-01T21:22:53ZengMDPI AGSensors1424-82202022-04-01228290610.3390/s22082906Acoustic Multi-Parameter Early Warning Method for Transformer DC Bias StateYuhao Zhou0Bowen Wang1International Education Institute, North China Electric Power University (Baoding), Baoding 071003, ChinaHebei Provincial Key Laboratory of Power Transmission Equipment Security Defense, North China Electric Power University (Baoding), Baoding 071003, ChinaThe acoustic signal in the operation of a power transformer contains a lot of transformer operation state information, which is of great significance to the detection of DC bias state. In this paper, three typical parameters used for DC bias state detection are selected by comparing the acoustic variation of a 500 kV Jingting transformer substation No. 2 transformer with that of the core model built in the laboratory; then, acoustic samples of the 162 EHV normal state transformers are collected, and the distribution regularity of three typical parameters in normal state is given. Finally, according to the distribution regularity, clear warning threshold of typical parameters are given, and the DC bias cases from the 500 kV Jingting transformer substation are used to verify the effectiveness of the threshold.https://www.mdpi.com/1424-8220/22/8/2906transformeracoustic detectionDC biasdata statistics |
| spellingShingle | Yuhao Zhou Bowen Wang Acoustic Multi-Parameter Early Warning Method for Transformer DC Bias State Sensors transformer acoustic detection DC bias data statistics |
| title | Acoustic Multi-Parameter Early Warning Method for Transformer DC Bias State |
| title_full | Acoustic Multi-Parameter Early Warning Method for Transformer DC Bias State |
| title_fullStr | Acoustic Multi-Parameter Early Warning Method for Transformer DC Bias State |
| title_full_unstemmed | Acoustic Multi-Parameter Early Warning Method for Transformer DC Bias State |
| title_short | Acoustic Multi-Parameter Early Warning Method for Transformer DC Bias State |
| title_sort | acoustic multi parameter early warning method for transformer dc bias state |
| topic | transformer acoustic detection DC bias data statistics |
| url | https://www.mdpi.com/1424-8220/22/8/2906 |
| work_keys_str_mv | AT yuhaozhou acousticmultiparameterearlywarningmethodfortransformerdcbiasstate AT bowenwang acousticmultiparameterearlywarningmethodfortransformerdcbiasstate |