Study and Application of BP Neural Network in Fault Diagnosing of Bearing

摘要：

Bearings are key components in various rotating machinery, and also one of the most easily damaged components. Their normal operating state is often a direct impact on the performance of the whole machine. The fault diagnosis of rolling bearing is of great significance. In this paper, the BP neural network based method for fault detection of rolling bearings is presented. The small sample, nonlinearity characteristics and self-learning capacity of BP Neural Network make it feasible to carry out fault diagnostic of bearing. Simulation results show that this method can effectively locate the bearing fault.

关键词： rolling bearing diagnosis PLC BP Neural Network

作者: Wei Tang Yunyun Yang

作者单位: Paper-making Engineering,Shaanxi University of Science and Technology,Xian,Shaanxi,710021,P.R.China Electrical and Electronic Engineering Institue Shaanxi University of Science and Technology Xian,P.

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 264-267

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）