TY  - JOUR
T1  - Three Phase Fault Diagnosis Based on RBF Neural Network Optimized By PSO Algorithm
AU - Sivakumar, M. AU - Parvathi, R.M.S. 
JO  - International Journal of Electrical and Power Engineering
VL  - 5
IS  - 4
SP  - 181
EP  - 185
PY  - 2011
DA  - 2001/08/19
SN  - 1990-7958
DO  - ijepe.2011.181.185
UR  - https://makhillpublications.co/view-article.php?doi=ijepe.2011.181.185
KW  - Three phase inverter circuit
KW  -fault diagnosis
KW  -PSO
KW  -RBF neural network
KW  -stimulus signal
KW  -India
AB  - 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.
ER  -