Fault trend prediction of mining machine gearbox based on wavelet analysis and ANN

摘要：

In this paper the vibration test system for the gearbox of mining machine , the wavelet denoising method , the artificial neural network s essential principles and its features, BP network structures model in the gearbox fault diagnosis are discussed.Tested vibration signals are disposed by the method of wavelet denoising and than as the inputs of BP neural network. By using classical BP neural network, four kinds of typical patterns of gearbox faults have been studied and diagnosed and satisfied results have been acquired. The research results indicate that BP neural network with the excellent abilities of parallel distributed processing, self-study, self-adaptation, self-organization,associative memory and its highly non-linear pattern recognition is an efficient and feasible tool to solve complicated state identification problems in the gearbox fault diagnosis simultaneously.

关键词： Artifical Neural Network(ANN) wavelet analysis Gearbox Fault diagnosis Back Propagation( BP) Algorithm

作者: YANG Shulian Li Wenhai HUA Zhen FANG Xiang KANG Zhenhua

作者单位: Computer department, ShanDong Institute of Business and Technology, YanTai 264005;Electronic Enginee Electronic Engineering department, Naval Aeronautical Engineering Institute,YanTai 264001 Computer department, ShanDong Institute of Business and Technology, YanTai 264005

会议类型: 国际会议

会议名称: 第七届国际测试技术研讨会

会议地点: 北京

会议语种:英文

在线出版日期: 2007-08-05（万方平台首次上网日期，不代表论文的发表时间）