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A TSK-Type Recurrent Neuro-Fuzzy Systems for Fault Prognosis
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作者 rafik mahdaoui Leila Hayet Mouss 《Journal of Software Engineering and Applications》 2012年第7期477-482,共6页
As a result from the demanding of process safety, reliability and environmental constraints, a called of fault detection and diagnosis system become more and more important. In this article some basic aspects of TSK (... As a result from the demanding of process safety, reliability and environmental constraints, a called of fault detection and diagnosis system become more and more important. In this article some basic aspects of TSK (Takigi Sugeno Kang) neuro-fuzzy techniques for the prognosis and diagnosis of manufacturing systems are presented. In particular, a neuro-fuzzy model that can be used for the identification and the simulation of faults prognosis models is described. The presented model is motivated by a cooperative neuro-fuzzy approach based on a vectorized recurrent neural network architecture. The neuro-fuzzy architecture maps the residuals into two classes: a one of fixed direction residuals and another one of faults belonging to rotary kiln. 展开更多
关键词 TSK NEURO-FUZZY Systems FAULTS DIAGNOSIS FAULT PROGNOSIS
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