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Proceedings Paper

Diagnostic model for mechanical wear state based on fuzzy neural network and its application
Author(s): Hua Liang; Mingzhong Yang
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Paper 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.

Paper Details

Date Published: 28 August 1995
PDF: 6 pages
Proc. SPIE 2620, International Conference on Intelligent Manufacturing, (28 August 1995); doi: 10.1117/12.217538
Show Author Affiliations
Hua Liang, Wuhan Institute of Technology (China)
Mingzhong Yang, Wuhan Institute of Technology (China)

Published in SPIE Proceedings Vol. 2620:
International Conference on Intelligent Manufacturing
Shuzi Yang; Ji Zhou; Cheng-Gang Li, Editor(s)

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