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

An integrated system for machine tool spindle head ball bearing fault detection and diagnosis

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)

Automatic detection and diagnosis systems have always attracted considerable interest in control engineering due to their positive effects of increasing safety and product quality in machinery condition monitoring and maintenance applications. Implementing automated detection and diagnosis has always been a challenge in rotating machines. In this article, we present the development of a strategy to detect and diagnose faulty bearings in a heavy-duty milling machine tool's spindle head and its implementation in a real machine. First, a comparison study of advanced methods for ball bearing fault detection in machine tool spindle heads is presented. Then, two automatic diagnosis procedures are compared: a fuzzy classifier and a neural network, which deal with different implementation questions involving the use of a priori knowledge, the computation cost, and the decision making process. The challenge is not only to be capable of diagnosing automatically but also to generalize the process regardless of the measured signals. Two actions are taken to achieve some kind of generalization of the application target: the use of normalized signals and the study of the Basis Pursuit feature extraction procedure. Finally, automatic monitoring system implementation on a real milling machine tool is presented.

Published in:

Instrumentation & Measurement Magazine, IEEE  (Volume:16 ,  Issue: 2 )

Date of Publication:

April 2013

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.