论文信息 - Gear Fault Diagnosis by Using Wavelet Neural Networks

Gear Fault Diagnosis by Using Wavelet Neural Networks

Fault diagnosis in gear train system is important in order to transmitting power effectively. The artificial intelligent such as neural network is widely used in fault diagnosis and already substituted for traditional methods such as kurtosis method, time analysis and so on. The symptoms of vibration signals in frequency domains have been used as inputs to the neural network and diagnosis results are obtained by network computation. This study presents gear fault diagnosis by using wavelet neural networks (WNN) and Morlet wavelet is used as the activation function in hidden layer of back-propagation neural networks (BPNN). Furthermore, the diagnosis results are compared within both methods of WNN and BPNN in four gear cases.

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