基于小波和神经网络的齿轮箱故障诊断  

Gearbox Fault Diagnosis Based on Wavelet and Neural Network

作　　者：张君东 潘宏侠[1] 刘春林[1] 

机构地区：[1]中北大学机械与动力工程学院

出　　处：《煤矿机械》2014年第8期268-270,共3页Coal Mine Machinery

基　　金：国家自然科学基金资助项目(50875247)

摘　　要：对齿轮箱故障诊断特点和方法进行分析,举例介绍了小波变换在齿轮箱故障诊断中的应用。利用小波变换对齿轮箱工况信号进行分解,重构以及提取细节信号包络谱,快速准确判断出齿轮箱设备运行状态是否异常,并利用BP神经网络进行故障诊断定位,比传统方法更有效。Analyzing the characteristics and the method of gearbox fault diagnosis, and give a example to introduce the application of wavelet transform in gearbox fault diagnosis. The wavelet transform can be used in the gearbox condition signal to decompose and reconstructed as well as extract the detail signal envelope spectrum, the operators can accurately and quickly determine wether the gearbox equipment operation is abnormal, and make use of BP neural network to locate the fault diagnosis. The method is more effective than traditional methods.

关 键 词：齿轮箱 故障诊断 小波变换 BP神经网络 

分 类 号：TH133.3[机械工程—机械制造及自动化]