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The Application of Neurofuzzy Systems in Intelligent Fault Diagnosis

Author Affiliations

  • 1Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kuala Lumpur, MALAYSIA

Res. J. Recent Sci., Volume 4, Issue (9), Pages 107-117, September,2 (2015)


Fault diagnosis is a crucial step in all industries to ensure high quality, cost efficiency, reliability as well as safety. As the complexity of the current machinery system is increasing, fault tolerance become more and more crucial. The conventional signal-based techniques can no longer detect fault occurrences effectively. A more analytical or knowledge-based approach is required in this case. The development of neurofuzzy system, a hybrid technology of fuzzy logic and artificial neural network, has made it to be suitable in intelligent fault diagnosis due to its high learning and adaptive capability. In this paper, the algorithm and architecture of fuzzy model, neural network and the neurofuzzy system are discussed. Its applications in machinery fault diagnosis are also addressed.


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