Abstract
Aiming at the problems of slow convergence and low diagnostic accuracy in back propagation (BP) neural network for fault diagnosis, this paper designs an improved double-adaptive-Bp neural network based on error pointer, optimizes its initial parameters by genetic algorithm (GA) and establishes a fault diagnosis model of improved BP (GA-IBP) neural network based on GA optimization. It uses the IGBT fault data in the inverter circuit as the training and test samples, and conducts simulation analysis through MATLAB. The results show that the improved algorithm has obvious effects on improving network convergence speed and diagnostic accuracy.
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