Diagnosis Method of High VoltageIsolating Switch Fault Based on Multi-SVDD under Incomplete Fault Type
Chen Shigang1, Guan Yonggang2, Zhang Xiaoqing1, Yang Yuanwei2, Zhang Yiming3
1. School of Electrical Engineering Beijing Jiaotong University Beijing 100044 China;
2. State Key Lab of Control and Simulation of Power Systems and Generation Equipments Department of Electrical Engineering Tsinghua University Beijing 100084 China;
3.Pinggao Group Co. Ltd Pingdingshan 467001 China
Focusing on the problem of incomplete fault types existing in high voltage isolating switch fault diagnosis, a fault diagnosis method based on multi-support vector domain description is proposed. Firstly, by principal component analysisto order the normal and known fault samples as a new eigenvector according to their contributions, and the weighted Gaussian kernel function was constructed with the contribution of features to improve the ability to identify inter type feature differences. Then the PSO was used to optimize the kernel parameters so that the model had a higher promotion ability and smaller false positive rate. Secondly, the normal and known fault samples were trained, the hypersphere describing the different working states of the isolating switch was established as the predictive model. Finally, the sample space was divided by multi support vector data description (Multi-SVDD) and the distance from the sample point to the center of the hypersphere was calculated to determine the type of sample. The experimental results showed that this method could effectively deal with the problem of incomplete fault samples in the fault diagnosis of high voltage isolating switch, and it could judge the unknown fault while diagnosing the known fault.
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