International Journal of Electrical and Power Engineering
ISSN: Online 1993-6001ISSN: Print 1990-7958
Abstract
The present study proposes a fault diagnosis methodology of three phase inverter circuit base on Radial Basis Function (RBF) artificial neural network trained by Particle Swarm Optimization (PSO) algorithm. Using the appropriate stimulus signal, fault features are extracted from efficient points in frequency response of the circuit directly and then a fault dictionary is created by collecting signatures of different fault conditions. Trained by the examples contained in the fault dictionary, the RBF neural network optimized by PSO has been demonstrated to provide robust diagnosis to the difficult problem of soft faults in three phase inverter circuits. The experimental result shows that the proposed technique is succeeded in diagnosing and locating faults effectively.
How to cite this article:
M. Sivakumar and R.M.S. Parvathi. Three Phase Fault Diagnosis Based on RBF Neural Network Optimized By PSO Algorithm.
DOI: https://doi.org/10.36478/ijepe.2011.181.185
URL: https://www.makhillpublications.co/view-article/1990-7958/ijepe.2011.181.185