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

作　　者：CHEN Chang zheng, LI Qing, SONG Hong ying Diagnosis and Control Center, Shenyang University of Technology, Shenyang 110023, P.R.China 

出　　处：《International Journal of Plant Engineering and Management》2001年第3期164-169,共6页国际设备工程与管理（英文版）

摘　　要：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.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.

关 键 词：wear particles identification fault diagnosis neural networks gray relationship 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]