Power System Fault Detection Using Wavelet Transform And Probability Neural Network

摘要

The identification of faults in any analog circuit is highly required toensure the reliability of the circuit. Early detection of faults in a circuit can greatly assist inmaintenance of the system by avo iding possibly harmful damage borne out of the fault. Anovel method for establishing a power fault using Wavelet transform and probability neural network. The Circuitunder Test (CUT) is three phase single level inverter. The transform coefficients for the fault freecircuit as well as for the simulated faults of CUT are found. The Wavelet transform is applied to theoutput of CUT and Standard Deviation (SD) of the transform coefficients are extracted. Using thetransform coefficients, fault dictionary has been formed. In order to identify the type of fault, a neuralnetwork classifier has been utilized. The compatibility of wavelet analysis with the variousclassification techniques for fault diagnosis has been illustrated in this paper. The results of the studydemonstrate the suitability and viability of wavelet analysis in fault diagnosis of power electroniccircuits.