Gearbox fault detection using neural networkjs technology

摘要

This paper describes the application of neural networks to gearbox fault diagnosis. In order to increase learning speed of BP network, a modified learningalgorithm was presented. Considering of the difficulty of choosing neural networks' architecture, genetic algorithm was employed. The discussion of the efefct of hidden layer nodes shows that with the increase of the number of nodes, the learning speed increase also yet result in poor generalization abiliyt. The test of fault tolernance ability tells that neural networks have 'bench type' tolerance ability. This ensures that when signals were contaminated by noise or feature extraction methods were not effective, the result can still be acceptable.