SDG multiple fault diagnosis by real-time inverse inference
| Autor: | Bei-ke Zhang, Chong-guang Wu, An-feng Li, Tao Xia, Zhao-qian Zhang |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Engineering
business.industry Inference Directed graph computer.software_genre Fault (power engineering) Industrial and Manufacturing Engineering Field (computer science) Expert system Combinatorial optimization Data mining Inference engine Safety Risk Reliability and Quality business computer Algorithm Combinatorial explosion |
| Zdroj: | Reliability Engineering & System Safety. 87:173-189 |
| ISSN: | 0951-8320 |
| Popis: | In the past 20 years, one of the qualitative simulation technologies, signed directed graph (SDG) has been widely applied in the field of chemical fault diagnosis. However, the assumption of single fault origin was usually used by many former researchers. As a result, this will lead to the problem of combinatorial explosion and has limited SDG to the realistic application on the real process. This is mainly because that most of the former researchers used forward inference engine in the commercial expert system software to carry out the inverse diagnosis inference on the SDG model which violates the internal principle of diagnosis mechanism. In this paper, we present a new SDG multiple faults diagnosis method by real-time inverse inference. This is a method of multiple faults diagnosis from the genuine significance and the inference engine use inverse mechanism. At last, we give an example of 65t/h furnace diagnosis system to demonstrate its applicability and efficiency. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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