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A Study on the Fault Diagnosis System for Combustion System of Diesel Engines Using Knowledge Based Fuzzy Inference  

유영호 (한국해양대학교 기계ㆍ정보공학부)
천행춘 (한국해양대학교 대학원)
Abstract
In general many engineers can diagnose the fault condition using the abnormal ones among data monitored from a diesel engine, but they don't need the system modelling or identification for the work. They check the abnormal data and the relationship and then catch the fault condition of the engine. This paper proposes the construction of a fault diagnosis engine through malfunction data gained from the data fault detection system of neural networks for diesel generator engine, and the rule inference method to induce the rule for fuzzy inference from the malfunction data of diesel engine like a site engineer with a fuzzy system. The proposed fault diagnosis system is constructed in the sense of the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HMH). The system is concerned with the rule reduction method of knowledge base for related data among the various interactive data.
Keywords
Fault Detecting; Fault Diagnosis; Malfunction Diagnosis Engine; Hierarchy of Malfunction Hypotheses;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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