A Fault Diagnosis Method Based on AR Parameter Fault Vector and Gray Neural Network
Dai Ya-ping · Jisuanji fangzhen · 2005
The problems of the traditional methods in which the energy integrals in frequency domain are taken as fault vector and trainable artificial net works are used as diagnosis network in practice use are talked about. And then a new rotary mechanism fault diagnosis method is proposed. AR parameters gotten from vibration signal data series are treated as the fault vector and gray neural network is introduced to detect the fault. The realization of this diagnosis system is described concretely. The diagnosis results of these methods are compared. Simulation shows that this method has advantages of simpler calculating steps and higher diagnosis validity.