Transformer fault diagnosis based on optimized FCM clustering by hybrid GA and PSO
XU Hai-ba · Power System Protection and Control · 2011
Optimized FCM clustering by hybrid GA and PSO(GAPSO-FCM) is introduced to diagnose the fault of transformer in order to conquer the shortages of FCM clustering,GA-FCM clustering and PSO-FCM clustering in transformer fault diagnosis. GAPSO-FCM clustering carries out global search,conquering the problem of FCM clustering easily falling into local minimum. According to the best global individual,GAPSO-FCM clustering makes GA algorithm and PSO algorithm organically link together, GA and PSO share a best individual,and the iterative process includes GA operation and PSO operation. It enlarges search area by the randomicity of GA,then searches more carefully according to PSO round the founded individual, conquering the premature problem of optimized FCM clustering based only on single GA or PSO. Simulation and case analysis indicate that GAPSO-FCM clustering for fault diagnosis is of higher accuracy than the other three kinds of clustering.