Acoustic Imaging Based Covariance Matrix Fitting Algorithm for Transformer Fault Diagnosis
Yue Feng, Yongliang Qian, Kunlun Wang, Zhixian Jiang · 2023
Power transformer is an essential part of modern power system, its stable and safe operation is very important to the healthy operation of power system. At present, the daily monitoring method of transformer is not perfect, but also needs the experience of on-site disposal personnel to judge. Therefore, in order to promote the development of power transformer fault diagnosis technology, it is necessary to develop new technology to further improve the accuracy and rapidity of fault diagnosis. Acoustic imaging as a sound field visualization technology has been widely concerned in the fault field. According to the principle and current situation of acoustic imaging, an acoustic imaging diagnosis technique of transformer fault based on covariance matrix fitting (CMF) algorithm is proposed in this paper. This method can accurately diagnose the fault state of transformer by the distribution of the sound field inside the transformer, so as to improve the fault diagnosis efficiency. At the same time, the acoustic test data of 7 power transformers with different voltage levels and different loads were used to test the method. The test results show that the acoustic imaging technology based on CMF algorithm can identify transformer faults accurately and quickly.