Application of Inverse Fuzzy Logical Inference to Breakdown Diagnosis

DOI

10.2991/jcis.2006.280How to use a DOI?

Keywords

Intelligent diagnosis, Fuzzy set, Breakdown causes, inverse logical inference

Abstract

In this paper, we present a search model, which divide symptoms into two sets, i.e., the positive symptom set (J1) and the negative symptom set (J2), to eliminate the causes of low possibility in the cause set to more effectively find various possible breakdown causes occurred during spinning process. The problem of diagnosis can be formulated in the form of the direct and inverse fuzzy logical inference. Application of the inverse logical inference in the expert systems of diagnosis is considered. Diagnosis decision finding requires fuzzy logical equations system solution. The developed diagnosis system by using fuzzy set theory can trace the possible breakdown causes in this paper. The diagnosis based on fuzzy logical equations can act as an expert consultant to facilitate the operator to trace the causes of breakdown at any time.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jeng-Jong Lin
PY  - 2006/10
DA  - 2006/10
TI  - Application of Inverse Fuzzy Logical Inference to Breakdown Diagnosis
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.280
DO  - 10.2991/jcis.2006.280
ID  - Lin2006/10
ER  -