Intelligent condition monitoring and fault diagnosis of a gearbox based on Artificial Neural Network

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: YangShulian Li Wenhai Zhen Hua Xiang Fang

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

会议类型: 国际会议

会议名称: 第八届国际电子测量与仪器学术会议(Proceedings of 2007 8th International Conference on Electronic Measurement & Instruments)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-08-16（万方平台首次上网日期，不代表论文的发表时间）