磨机减速机滚动轴承特征提取和故障诊断研究

Research on fault diagnosis and feature extraction for rolling bearings of mill gearbox

滚动轴承是水泥磨机减速机的核心组件,同时也是故障频发的部件之一,为保证其健康、安全、高效的运行,本文将独立分量分析(ICA)与支持向量机(SVM)方法结合,为磨机减速机滚动轴承的故障诊断提供一个新的思路。首先提取轴承不同故障状态下观测信号的独立分量,再对独立分量(ICA)进行奇异值分解从而得到特征信息,最后联合支持向量机(SVM)将特征信息进行故障识别。数据处理结果表明这种特征提取的方法是有效的。

Rolling bearing is not only one of the mill reducer＇ s core components, but also one of components which tend to fail. In or- der to make it work in health, safety, efficience. This paper presents an intelligent method combined Independent Component Analy- sis（ICA） and Support Vector Machine（SVM） for rolling bearing＇ s fault diagnosis. Firstly, the independent components are extracted from observed signals in different faults state.Secondly, singular value decomposition to the extracted independent components is treat- ed as eisertvalues.Fiualty, the ei^envalues can be classified based on Support Vector Machine（SVM）.The data processing shows the method introduced in this paper is effective.