Abstract
Reducer failure was analyzed and by use of BP neural network in the paper. Model of failure diagnosis was established. By using genetic algorithms, the value of neural networks, the threshold, and the network structure were optimized. Genetic neural network model was applied to the system design of remote reducer fault diagnosis. To compare training error curve of BP neural network with genetic neural network, it was shown that genetic neural network in the training of speed and accuracy higher than the neural network training model.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.