Wear Fault Diagnosis of Machinery Based on Neural Networks and Gray Relationships

In this paper, the regular characteristic of wear particles related to fault type of machines based on condition monitoring of reciprocal machinery is discussed. The typical wear particles spectrum is established according to the equipment structure, friction and wear rule and the characteristic of wear particles; The identification technology of wear particles is proposed based on neural networks and a gray relationship; an intelligent wear particles identification system is designed. The diagnosis example shows that this system can promote the accuracy and the speed of wear particles identification.