Induction motor fault detection and diagnosis using supervised and unsupervised neural networks
作者： S. Premrudeepreechacharn , T. Utthiyoung , K. Kruepengkul , P. Puongkaew
DOI: 10.1109/ICIT.2002.1189869
关键词: Unsupervised learning 、 Induction motor 、 Artificial neural network 、 Supervised learning 、 Machine learning 、 Engineering 、 Fault detection and isolation 、 Artificial intelligence 、 Condition monitoring 、 Fault (power engineering)
摘要: Successful and reliable motor fault detection diagnosis requires expertise knowledge. Neural network technologies can be used to provide inexpensive but effective mechanism This paper presents two neural networks algorithms: supervised unsupervised types with applications induction problems. The algorithm was simulated its performance verified on various types. Simulation results illustrated that, after training the network, system is able detect faulty machine.
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