Abstract
According to asynchronous motor's complex fault characteristics, and the combination of wavelet transform technique, an improved wavelet neural network for fault diagnosis of asynchronous motor is proposed in this paper. Taking wavelet transform technique as wavelet neural network (WNN) the input vector of picking up asynchronous motor's the characteristic signal, and wavelet neural network algorithm is optimized, The self-adaptive wavelet neural network algorithm about adjusting momentum vector alter-learning rate is proposed and given the momentum coefficient and alter-learning rate adjustment method. Through the actual testified results show that the method is effective and feasible, and has a better diagnostic accuracy, fast and generalized performances.
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.
