Application of Inverse Fuzzy Logical Inference to Breakdown Diagnosis
Jeng-Jong Lin 0
0Department of Information Management, Vanung University
Available Online October 2006.
- https://doi.org/10.2991/jcis.2006.280How to use a DOI?
- Intelligent diagnosis, Fuzzy set, Breakdown causes, inverse logical inference
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jeng-Jong Lin PY - 2006/10 DA - 2006/10 TI - Application of Inverse Fuzzy Logical Inference to Breakdown Diagnosis BT - 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 - https://doi.org/10.2991/jcis.2006.280 ID - Lin2006/10 ER -