Abstract
A modified particle swarm optimization--compound model PSO with stochastic inertia weigh is put forward and used to optimize the parameters of wavelet neural network. The trained wavelet neural-network is applied to the fault diagnosis experiment of gearbox. The experimental result indicates that the wavelet neural-network training method based on the modified PSO is effective. This is an available approach to solve the problems on condition monitoring and fault diagnosis.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
