A method for fault diagnosis of power transformers

Abstract

The invention discloses a power transformer fault diagnosis method. The power transformer fault diagnosis method comprises the following steps of determining N fault types of a transformer, and determining corresponding fault characteristic quantities for diagnosing the N fault types; taking the fault characteristic quantities corresponding to the N fault types as a testing sample, and performing normalizing processing of testing sample data; combining any two of the N fault types, establishing X (described in the specification) SVM ( Support Vector Machine) secondary classifiers, and training the X SVM secondary classifiers, and optimizing a SVM kernel function using a method based on combination of K-fold cross validation and an artificial bee colony algorithm; calculating generalization errors of each SVM classifier according to the K-fold cross validation method; and diagnosing the N fault types using an improved reordering adaptive directed acyclic graph support vector machine method. The invention has a capability of well diagnosing the fault type of a transformer, can greatly improve the accuracy of transformer fault diagnosis, and provides a reliable basis for transformer maintenance.

Description

technical field [0001] The invention relates to a power transformer fault diagnosis method, which belongs to the technical field of power equipment state detection. Background technique [0002] Judging the operating state of the transformer and its latent faults, so as to discover the nature and development trend of the internal faults of the transformer in time is of great significance for mastering the operating state of the transformer and the safe and stable operation of the power system. DGA (dissolved gas analysis) method is currently one of the most effective and simple methods to find early internal faults in oil-immersed transformers. Among them, the IEC three-ratio method has made a great contribution to discovering latent faults of transformers in the past equipment maintenance. However, in long-term practice, it is found that a considerable part of the DGA results of this method are not covered in this code, which leads to the inability to diagnose some faults....

AI Technical Summary

Problems solved by technology

However, there is room for further improvement in the algorithm

Images