Corrosion fault identification model of substation grounding grid based on PSO-LS-SVM

Abstract

As one of the important equipment to ensure the normal operation of substation, the performance of grounding grid has been highly concerned. In recent years, researchers propose that the theory of electromagnetic induction can be used to diagnose and identify the corrosion fault of substation grounding grid. In this paper, a fault classification model based on LS-SVM optimized by PSO is proposed to identify the corrosion fault of grounding grid. Firstly, the wavelet packet transform principle is used to filter the original data, and the wavelet packet energy is used to construct the fault eigenvalue as the input of the fault classification model. Based on LS-SVM, a corrosion fault classification model is constructed, and particle swarm optimization method is used to optimize the parameters of the model, which solves the problem of traditional SVM parameter optimization. Through the practical application in substation, the model proposed in this paper can identify the corrosion of grounding grid conductor without excavation and power failure, which provides an effective scheme for engineering application.