Status Assessment of Secondary Equipment in Substation Based on Fuzzy Comprehensive Support Vector Machine Method

In this paper, a status assessment model based on fuzzy comprehensive support vector machine (FC-SVM) is proposed for the scientific basis in the maintenance of secondary equipment in substation is insufficient. Then, an effective utilization and information extraction of various assessment factors is achieved by using fuzzy comprehensive assessment method (FCA) and the secondary equipment status is assessed via SVM on the basis of the online alarm information and offline information. Experiment analysis is carried out on three different kernel functions and the radial basis function (RBF) is selected as the kernel function for the proposed model in the assess process of SVM. Experimental results show that the status assessment accuracy of secondary equipment is improved by using FC-SVM.