Research on transformer fault diagnosis method based on principal component analysis and grey correlation analysis

As one of the most important electrical equipment in the power system, the operation status of power transformers directly affects the safe and stable operation of the whole power system. In order to effectively locate the faults of power transformers accurately and improve the accuracy and stability of diagnosis, this paper proposes a transformer evaluation method based on principal component analysis and gray correlation analysis. The method applies the principal component analysis to determine the weights, then dimensionless processing of sample data, followed by bringing the indicator weights and the correlation coefficient matrix derived from the dimensionless processing into the gray weighted correlation, and judging the transformer fault type by finding the gray weighted correlation of the sample data. After the example application, the calculation results show the effectiveness and objectivity of this method for fault diagnosis of transformer, and it is of value to propose new ideas for transformer evaluation.