Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric Correlation
Traditional high-voltage reactor monitoring and diagnosis research has problems such as high sampling demand, difficulty in noise reduction on site, many false alarms, and lack of on-site data. In order to solve the above problems, this paper proposes an acoustic–electric fusion high-voltage reactor...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-09-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/15/19/7196 |
| _version_ | 1797479519844564992 |
|---|---|
| author | Shuguo Gao Chao Xing Zhigang Zhang Chenmeng Xiang Haoyu Liu Hongliang Liu Rongbin Shi Sihan Wang Guoming Ma |
| author_facet | Shuguo Gao Chao Xing Zhigang Zhang Chenmeng Xiang Haoyu Liu Hongliang Liu Rongbin Shi Sihan Wang Guoming Ma |
| author_sort | Shuguo Gao |
| collection | DOAJ |
| description | Traditional high-voltage reactor monitoring and diagnosis research has problems such as high sampling demand, difficulty in noise reduction on site, many false alarms, and lack of on-site data. In order to solve the above problems, this paper proposes an acoustic–electric fusion high-voltage reactor acquisition system and defect diagnosis method based on reactor pulse current and ultrasonic detection signal. Using the envelope peak signal as the basic detection data, the sampling requirement of the system is reduced. To fill the missing data with partial discharge (PD) information, a method based on k-nearest neighbor (KNN) is proposed. An adaptive noise reduction method is carried out, and a noise threshold calculation method is given for the field sensors. A joint analysis method of acoustic and electrical signals based on correlation significance is established to determine whether a discharge event has occurred based on correlation significance. Finally, the method is applied to a UHV reactor on the spot, which proves the effectiveness of the method proposed in this paper. |
| first_indexed | 2024-03-09T21:46:44Z |
| format | Article |
| id | doaj.art-6145ee6d39ed43f9856ca7202f1d1549 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T21:46:44Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-6145ee6d39ed43f9856ca7202f1d15492023-11-23T20:14:47ZengMDPI AGEnergies1996-10732022-09-011519719610.3390/en15197196Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric CorrelationShuguo Gao0Chao Xing1Zhigang Zhang2Chenmeng Xiang3Haoyu Liu4Hongliang Liu5Rongbin Shi6Sihan Wang7Guoming Ma8State Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, ChinaState Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, ChinaState Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, ChinaState Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, ChinaState Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, ChinaState Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaTraditional high-voltage reactor monitoring and diagnosis research has problems such as high sampling demand, difficulty in noise reduction on site, many false alarms, and lack of on-site data. In order to solve the above problems, this paper proposes an acoustic–electric fusion high-voltage reactor acquisition system and defect diagnosis method based on reactor pulse current and ultrasonic detection signal. Using the envelope peak signal as the basic detection data, the sampling requirement of the system is reduced. To fill the missing data with partial discharge (PD) information, a method based on k-nearest neighbor (KNN) is proposed. An adaptive noise reduction method is carried out, and a noise threshold calculation method is given for the field sensors. A joint analysis method of acoustic and electrical signals based on correlation significance is established to determine whether a discharge event has occurred based on correlation significance. Finally, the method is applied to a UHV reactor on the spot, which proves the effectiveness of the method proposed in this paper.https://www.mdpi.com/1996-1073/15/19/7196relevance significancereactor defectjoint diagnosisk-nearest neighborsadaptive noise reduction |
| spellingShingle | Shuguo Gao Chao Xing Zhigang Zhang Chenmeng Xiang Haoyu Liu Hongliang Liu Rongbin Shi Sihan Wang Guoming Ma Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric Correlation Energies relevance significance reactor defect joint diagnosis k-nearest neighbors adaptive noise reduction |
| title | Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric Correlation |
| title_full | Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric Correlation |
| title_fullStr | Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric Correlation |
| title_full_unstemmed | Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric Correlation |
| title_short | Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric Correlation |
| title_sort | early warning of high voltage reactor defects based on acoustic electric correlation |
| topic | relevance significance reactor defect joint diagnosis k-nearest neighbors adaptive noise reduction |
| url | https://www.mdpi.com/1996-1073/15/19/7196 |
| work_keys_str_mv | AT shuguogao earlywarningofhighvoltagereactordefectsbasedonacousticelectriccorrelation AT chaoxing earlywarningofhighvoltagereactordefectsbasedonacousticelectriccorrelation AT zhigangzhang earlywarningofhighvoltagereactordefectsbasedonacousticelectriccorrelation AT chenmengxiang earlywarningofhighvoltagereactordefectsbasedonacousticelectriccorrelation AT haoyuliu earlywarningofhighvoltagereactordefectsbasedonacousticelectriccorrelation AT hongliangliu earlywarningofhighvoltagereactordefectsbasedonacousticelectriccorrelation AT rongbinshi earlywarningofhighvoltagereactordefectsbasedonacousticelectriccorrelation AT sihanwang earlywarningofhighvoltagereactordefectsbasedonacousticelectriccorrelation AT guomingma earlywarningofhighvoltagereactordefectsbasedonacousticelectriccorrelation |