Diagnostic model for mechanical wear state based on fuzzy neural network and its application

Hua Liang; Mingzhong Yang

doi:10.1117/12.217538

28 August 1995 Diagnostic model for mechanical wear state based on fuzzy neural network and its application

Hua Liang, Mingzhong Yang

Proceedings Volume 2620, International Conference on Intelligent Manufacturing; (1995) https://doi.org/10.1117/12.217538
Event: International Conference on Intelligent Manufacturing, 1995, Wuhan, China

Abstract

An intelligent diagnostic model for mechanical wear state based on a fuzzy neural network is proposed. The model can handle input features presented in quantitative and/or linguistic form and classify patterns in terms of fuzzy class membership values. This allows efficient modeling of fuzzy diagnosis of mechanical wear state in terms of the Ferrogram Analysis Report Sheet. The application of the model to the diagnosis of wear state of diesel engines is demonstrated. The results are very satisfactory.

Citation Download Citation

Hua Liang and Mingzhong Yang "Diagnostic model for mechanical wear state based on fuzzy neural network and its application", Proc. SPIE 2620, International Conference on Intelligent Manufacturing, (28 August 1995); https://doi.org/10.1117/12.217538

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available