Fault Diagnosis Of Gear-Box Based On Wavelet Neural Network

With the appearance of tandem rolling, the rolling mills become more and more large-sized,sequential and roboticized. Once the gearing of rolling mill breaks down, the whole rolling mill will be unable to work normally, and the economic losses will be enormous. In the fault of rolling mill's gearing system, gear-box's fault holds a large proportion.There are many methods about fault diagnosis, such as vibration diagnosis,acoustics diagnosis,oil sample analysis and so on. Viabration analysis is widely used in the condition monitoring and fault diagnosis of the gear-box system, and also is the most effective method. Analysing the viabration signal of gear and bearing is the main work of the dissertation.In the dissertation, the mechanism of gear-box's vibration is studied, and the reason of fault is found out. And through the theory of de-noise, the high frequency noise is excluded and the characteristic signal frequency band is abstracted.Wavelet neural network which is based on wavelet analysis rationale is a sort of new neural network. It incorporates the time-frequency character of the wavelet analysis and the self-study function of the neural network. In the paper, the wavelet neural network is applied in fault diagnosis of the gear-box. The results of the experimentation show that the wavelet neural network which is applied in fault diagnosis will increase the accuracy and will have a good develop tendency.The intelligentized diagnosis program is designed which combines nnToolKit neural network toolbox with MATLAB and Visual C++. The program , which gets rid of MATLAB and VC environment, has humanization interface , is easy to work and install.