独立分量分析在齿轮箱故障诊断中的应用  

Application of Independent Component Analysis to Fault Diagnosis of Gearbox

作　　者：黄晋英[1] 毕世华[1] 潘宏侠[2] 杨喜旺[3] 

机构地区：[1]北京理工大学宇航科学技术学院,北京100081 [2]中北大学机械工程与自动化学院,太原030051 [3]中北大学电子与计算机科学技术学院,太原030051

出　　处：《振动．测试与诊断》2008年第2期126-130,共5页Journal of Vibration,Measurement & Diagnosis

基　　金：国家自然科学基金资助项目(编号:50575214);山西省自然科学基金资助项目(编号:2007011070)

摘　　要：提出了一种用于齿轮箱故障诊断的信号预处理方法。推导了基于互信息最小化的独立分量分析算法(简称ICA算法),应用确定性混合信号对算法进行了仿真验证,并将该算法应用于齿轮箱振动信号的预处理中。经3种工况下的齿轮箱振动信号的ICA分解结果分析,表明应用ICA技术后,故障信息得到了极大的增强。改变了传统的以降噪为主的故障信息增强思想,为微弱故障的有效诊断提供了一定的技术手段。A signal preprocessing method based on independent component analysis(ICA) is put forword for fault diagnosis of a gearbox.The ICA algorithm based on mutual information minimization is derived and verified by mixed deterministic signals.Vibration signals measured from the gearbox are decomposed by ICA and it shows that the source signals have obvious fault characteristics.The fault information is enhanced when the ICA technology is applied to the fault diagnosis of the gearbox,which changes the traditional way of enhancing fault information mainly by reducing measurement noise,and provides a method for the diagnosis of weak faults.

关 键 词：独立分量分析 齿轮箱 故障诊断 信息增强 

分 类 号：TH133[机械工程—机械制造及自动化] TH115