Research On Power Equipment Fault Diagnosis Method Based On Information Fusion Technology

Nowadays,electric is closely related to human life and production.Subsequently,with the increasing scale and complexity of power grid,ensuring the safe and stable operation of power equipment is the foundation of power grid safety.As the most common power equipment,transformer is most prone to malfunction,and it is also cause a great loss and difficult to repair.This paper focuses on the method of transformer fault diagnosis,and studies the diagnosis method based on multi source information fusion.The main work of this thesis are as follows:To address the low accuracy and low stability of a single algorithm for transformer fault diagnosis,this dissertation is based on multi feature fusion diagnosis algorithm by combing support vector machine(SVM)and D-S evidence theory,The way to construct the basic probability assignment(BPA)of evidence has been improved by calculating the correct recognition rate and misdiagnosis probability of the SVM classification results.Simulation results show that this method can obtain more reliable belief function of the evidence,and further improve the accuracy of multi-feature fusion fault diagnosis.In the process of transformer fault diagnosis based on support vector machine(SVM),unbalanced data makes the classifying hyper plane of SVM shift to the minority samples,which decreases the diagnostic accuracy.To solve this problem,a method combining over sampling strategy and SVM is proposed.After extracting the boundary samples from the minority samples,The boundary samples extracted from the minority samples are sampled up to generate the new random samples.These new samples are added into the minority samples to make the two kinds of samples balanced.Comparing the performance of SVM classification model with balanced data and unbalanced data,the experimental results show that this method can effectively reduce the deviation of SVM classifying hyper plane.Finally,the research of this paper is summarized and analyzed,and the future research direction of power equipment fault diagnosis is discussed.