ABSTRACT A converter transformer is one of the most widely used power equipment. This paper proposes a statistical dissolved gas analysis (DGA) diagnosis method to evaluate the occurrence and type of the discharge starting stage of the converter transformer based on a statistical analysis of the gas generation amount in the converter transformer oil during operation. The method is similar to case retrieval in case‐based reasoning (CBR). The basic data, which are corresponding to the case base, are sample populations consisting of the model test data for the gas generation amount at the discharge starting stage of typical discharge models with oil‐paper insulation under various AC‐DC composite voltage ratios. The diagnosis method, which is corresponding to the case retrieval, is a robust statistical analysis. The typical discharge models are column‐plate, air gap, suspension, and needle‐plate electrode models. By the statistical DGA diagnosis, we can obtain the diagnosis probability density values and the statistical hypothesis test results for the occurrence and type of the discharge starting stage. We experimentally verified the effectiveness of the proposed method with the test data of each typical discharge model for the AC‐DC composite voltage ratios of 1:1, 1:3, and 1:5.
An et al. (Thu,) studied this question.