Fault Diagnosis Research of TWERD Frequency Converter Based on Wavelet Transform

Abstract

Taking TWERD frequency converter as research object, the working principle and fault types of three-phase SPWM inverter are analyzed. Its output line voltage waveform in normal operation and fault condition is studied. According to the fault information and the different data of input and load changes, the frequency converter output line voltage waveform is decomposed by wavelet transform. The low frequency energy value is picked-up and regards it as eigenvector. The mapping relationship between eigenvector and fault types are established by BP neural network, the fault bridge and fault location of frequency converter are found. Simulation results show that the diagnosis accuracy is 96.5% after training 46 times. Fast convergence speed and high precision is obtained.