Acoustic Multi-Parameter Early Warning Method for Transformer DC Bias State

Abstract

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.