Neural network electrical machine faults diagnosis based on multi-population GA
Zaiping Chen, Yueming Zhao, Yang Zheng, Rui Lou · 2008
A hybrid method combining artificial neural network (ANN) with genetic algorithm (GA) is discussed in this paper. A new strategy of optimization on ANN structure and weights based on multi-population GA is proposed, and the quantitative optimization of ANN is realized. The Levenberg-Marquardt(LM) algorithm is used for further training the neural network, which can avoid the weak local searching ability of GA and shows both of the merits of GA as well as ANN. In this paper, the algorithm proposed is employed in the electrical machine fault diagnosis, and the simulation results verified the correctness and effectiveness of the scheme proposed.