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Gear Fault Diagnosis with Neural Network Based on Niche Genetic Algorithm

Because of the complexity of gear working condition, there are non-linear relationship between characteristic parameters and fault types. This paper proposes to apply the artificial neural network theory and the genetic algorithm to solve the difficulties of gear fault diagnosis. Niche technique based on crowding mechanism is used in genetic algorithm, and punishing function is adopted to adjust individual fitness, so as to promote global search capability. Taking a certain gearbox fault signal acquisition experimental system for an example, Matlab software and its neural network toolbox are used to model and simulate. The experiment result shows that the founded network model has good performance for the common gear fault diagnosis and it can identify various types of faults stably and accurately.