Fault Diagnosis Method of Transmission Line Based on VMD-FOA-LSSVM
To address the issue of low accuracy of existing diagnostic methods in diagnosing short circuit faults on transmission lines,a fault diagnosis method of transmission lines based on VMD-FOA-LSSVM is proposed.Firstly,the three-phase fault voltage data are decompose with VMD to acquire a series of modal components.The sample entropy values of each modal component are obtained respectively,and the sample entropy values are used to compose the fault feature set.Then,the fruit fly optimization algorithm(FOA)is improved by changing the step size,so as to strengthen its global search ability of the algorithm.Then the improved FOA is used to optimize the least squares SVM classification model to further improve the classification performance of the model.Finally,the fault feature set is put into FOA-LSSVM model for further training,and compared with several common fault diagnosis methods.The experimental results show that FOA-LSSVM method has higher accuracy in transmission line fault diagnosis,and can diagnose transmission line faults more accurately and quickly.
万方数据
维普
