제어로봇시스템학회:학술대회논문집
- 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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- Pages.109-114
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- 1993
Multiple fault diagnosis method using a neural network
- Lee, Sanggyu (Process Systems Laboratory, Dept. of Chem. Eng. KAIST) ;
- Park, Sunwon (Process Systems Laboratory, Dept. of Chem. Eng. KAIST)
- 발행 : 1993.10.01
초록
It is well known that neural networks can be used to diagnose multiple faults to some limited extent. In this work we present a Multiple Fault Diagnosis Method (MFDM) via neural network which can effectively diagnose multiple faults. To diagnose multiple fault, the proposed method finds the maximum value in the output nodes of the neural network and decreases the node value by changing the hidden node values. This method can find the other faults by computing again with the changed hidden node values. The effectiveness of this method is explored through a neural-network-based fault diagnosis case study of a fluidized catalytic cracking unit (FCCU).
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