Title: Research on the Neural Network in Rotating Machinery Fault Diagnosis
Abstract: BP neural network is effective for dealing with non-liner mapping which could describe the relations between frequency characters and faults.Probabilistic neural network(PNN) is simple in learning rules and rapid in training,which could void the problems of the local optimization and the repeating training.Two models for rotation machinery fault diagnosis are established by using appropriate parameters according to the theory of two neural networks.The fault data of some rotation machineries is dealt with by using the models,and the result shows the applied value of the neural networks in the fault diagnosis.Comparing the result of the fault data,PNN neural network is better than BP neural network in the fault-tolerant capability.
Publication Year: 2008
Publication Date: 2008-01-01
Language: en
Type: article
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Cited By Count: 2
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