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- W3128691212 abstract "Abstract This paper describes the application of neural networks to gearbox fault diagnosis. In order to increase learning speed of BP network, a modified learning algorithm was presented. Considering of the difficulty of choosing neural networks’ architecture, genetic algorithm was employed. The discussion of the effect of hidden layer nodes shows that with the increase of the number of nodes, the learning speed increase also yet result in poor generalization ability. The test of fault tolerance 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. To test the performance of the application of neural networks on gearbox fault diagnosis, experiments of single fault and multi-faults were both implemented and diagnosed by neural networks. The results were satisfied." @default.
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- W3128691212 date "1999-09-12" @default.
- W3128691212 modified "2023-09-25" @default.
- W3128691212 title "Gearbox Fault Detection Using Neural Networks Technology" @default.
- W3128691212 doi "https://doi.org/10.1115/detc99/vib-8329" @default.
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