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A diagnosis method basing on neural network classifier, genetic algorithm (GA) and wavelet transform is proposed for a pulse width modulation voltage source inverter. It is used to detect and identify the transistor open-circuit fault. BP neural network (BPNN) is capable of recognition. However, it has shortcomings obviously. These are just advantages of GA, which has ability of global search. Thus...
As the shortcomings of BP neural network slow convergence rate, falling into local minimum easily and difficult to determine the number of hidden nodes accurately, the number of hidden nodes, weights and threshold of BP neural network were optimized, using binary and real number hybrid coding based on genetic algorithms with global searching ability. Finally, the method tested with WD615 diesel engine...
To solve the traditional fault diagnosis can not be adapted to the complicated system, a kind of new multi-sensor fusion fault diagnosis method is presented. The method applies the theory of genetic algorithms and fuzzy logic to the BP (back propagation) neural network. Combined with BP and GA, it walks in several steps. Firstly, the best individual is chosen in current population and trained in order...
The proposed method is adopted by genetic algorithm and BP neural network combine together, so GA-BP network is structured and used to the study of fault model and fault diagnose. It combines the ability of genetic algorithm with global optimizing and neural network with learning and memory, and resolves to problems that are slowly study speed and local minimum solution to produce easily for the BP...
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