Application of Wavelet Analysis in Fault Diagnosis of Power Cable

Abstract

If the fault location on the power cable can't be quickly found and eliminated in time, it will cause the interruption of electricity for domestic use and power supply for industrial and mining production, resulting in economic losses. Therefore, combining wavelet transform with decision tree, random forest and SVM (support vector machine), this study proposes a method to identify cable faults, and builds the corresponding cable fault model in MATLAB. The simulation results of the model show that the model can greatly improve the calculation efficiency of cable fault, can quickly identify and accurately locate the fault, and has higher accuracy than other traditional identification methods, which can be widely used in online real-time accurate monitoring and diagnosis of cable fault.