Cart (Loading....) | Create Account
Close category search window
 

Mechano-electric system fault diagnosis based on wavelet analysis and neural networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Chen Changzheng ; Diagnosis & Control Center, Shenyang Univ. of Technol. ; Guo Yi ; Wang Nan ; Wang Yi

According to the trend of intelligence fault diagnosis and the variety of information provided by the equipment, the idea of integrated neural networks used in fault diagnosis is put forward in this paper for the first time, and the correlated questions about the new idea is also researched, such as how to model, how to realize, etc. It provides a new method for fault diagnosis. Integrated neural networks can be used to diagnose faults from different levels and different aspects, so it is conform to the actual situation well. In the paper wavelets' applications in fault diagnosis is given. Here wavelet is used as a tool of signal processing. By applying wavelets analyzing, one kind of new feature vector reflecting the faults is gotten, which can be used by neural networks as its training mode. This paper presents an intelligent methodology for diagnostics of incipient faults in rotating machinery. A fault diagnosis system is developed for rotating machinery. In this system, the wavelet transform techniques are used in combination with function approximation model to extract fault features used in the fault diagnosis of rotating machinery

Published in:

Electrical Machines and Systems, 2005. ICEMS 2005. Proceedings of the Eighth International Conference on  (Volume:3 )

Date of Conference:

29-29 Sept. 2005

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.