0
TECHNICAL BRIEFS

A Fuzzy Decision System for Fault Classification Under High Levels of Uncertainty

[+] Author and Article Information
Yubao Chen

Department of Industrial and Manufacturing Systems Engineering, University of Michigan-Dearborn, Dearborn, MI 48128-1491

J. Dyn. Sys., Meas., Control 117(1), 108-115 (Mar 01, 1995) (8 pages) doi:10.1115/1.2798516 History: Received April 01, 1993; Online December 03, 2007

Abstract

The problem of high levels of uncertainty existing in machine diagnosis is addressed by an approach based on fuzzy logic. In this approach, multiple sensors/channels are used, and the uncertainty is treated by membership functions in different stages of the signal processing. The concepts of fuzziness, fuzzy set, and fuzzy inference are described, particularly for the development of a practical procedure for machine diagnosis. The membership functions are established through a learning process based on test data, rather than being selected a priori. The information-gain weighting functions are also introduced in order to improve the robustness and reliability of this method. As a result, a framework of a Fuzzy Decision System (FDS) is proposed and applied to a machining process. Experiment verification with an optimistic success rate of 97.5 percent was achieved.

Copyright © 1995 by The American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.

References

Figures

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In