Application of a optimized wavelet neural networks in rolling bearing fault diagnosis

摘要：

　　According to the fault type and fault signal of rolling bearing is difficult to predict, the paper proposed a new method to diagnose fault of rolling bearings with the wavelet neural network optimizated by simulated annealing particle swarm optimization.And it was applied to the fault diagnosis of rolling bearing.The experiment shows that this method can reduce the iteration time and improve the accuracy of convergence.

关键词： fault diagnosis optimization of wavelet network rolling bearing

作者: Lin Yuanyan Wang Binwu

作者单位: Department of Mechanical Engineering,Guilin College of Aerospace Technology,Guilin,Guangxi 541004,P.R.China

会议类型: 国际会议

会议名称: the 3nd International Conference on Digital Manufacturing & Automation (第三届数字制造与自动化国际会议(ICDMA 2012))

会议地点: 桂林

会议语种:英文

页码: 919-922

在线出版日期: 2012-08-01（万方平台首次上网日期，不代表论文的发表时间）