Acoustic Diagnosis of Partial Discharges in Transformers

被引：0

作者：

Huang Shan ^{[1
]}

Liu Hongjing ^{[1
]}

Qin Huan ^{[1
]}

Qiu Shou ^{[2
]}

Jian Wei ^{[2
]}

Miao Wang ^{[1
]}

Wu Linlin ^{[1
]}

Liu Kewen ^{[1
]}

Wu Guoxin ^{[3
]}

Li Min ^{[3
]}

机构：

[1] State Grid Beijing Elect Power Co Elect Power Res, Beijing 102206, Peoples R China

[2] Bejing Zhongtai Huadian Sci & Technol Co Ltd, Beijing 102206, Peoples R China

[3] North China Elect Power Univ, Beijing 102206, Peoples R China

来源：

2020 IEEE CONFERENCE ON ELECTRICAL INSULATION AND DIELECTRIC PHENOMENA (2020 IEEE CEIDP) | 2020年

关键词：

FAULTS;

D O I：

10.1109/CEIDP49254.2020.9437381

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Partial discharge in the transformer may generate noise. In view of this characteristic, it is proposed to apply the audio detection method to the diagnosis of partial discharge. Discharge faults in the transformer were simulated, and a method for diagnosis of these faults based on audio is studied. Three models for typical partial discharges are designed, namely the plate electrode discharge, the pin plate electrode discharge and the surface discharge. The audio produced by these discharges was recorded and hence an abnormal audio database was built. Using wavelet packet algorithm, audio features of partial discharge are extracted, and then the neural network algorithm is used to distinguish one kind of discharges from others successfully.

引用

页码：556 / 559

页数：4

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