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- W1560001257 abstract "The early detection of faults (just beginning and still developing) can help avoid system shutdown, breakdown and even catastrophes involving human fatalities and material damage. Computational intelligence techniques are being investigated as an extension to the traditional fault diagnosis methods. This paper discusses the neuro-fuzzy approach to modelling and fault diagnosis, based on the TSK/Mamdani approaches. An application study of an electro-pneumatic valve actuator in a sugar factory is described. The key issues of finding a suitable structure for detecting and isolating ten realistic actuator faults are outlined." @default.
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- W1560001257 date "2002-01-01" @default.
- W1560001257 modified "2023-09-27" @default.
- W1560001257 title "Fault Diagnosis of an Electro-pneumatic Valve Actuator Using Neural Networks With Fuzzy Capabilities" @default.
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