独立分量分析及其在故障诊断中的应用

独立分量分析是盲源分离的一种新方法，其处理的对象是相互统计独立的信号源经线性组合而产生的一组混合信号，最终目的是从混合信号中分离出各独立的信号分量。本简要介绍了独立分量分析的基本思想及算法，并对现场采集到的多组振动信号进行了分析，结果表明，独立分量分析在对混合信号进行盲分离方面具有很强的能力，从而为机械设备状态监测与故障诊断提供了一种行之有效的信号预处理的新方法。

Independent Component Analysis and Its Applications to Fault Diagnosis

As a new approach of blind source separation(BSS),independent component analysis(ICA) is a recently developed method in which the processed objects are mixed signals from linear combination of the original data,and the goal is to separate the source from the mixtures and the components separated are statistically independent,or as independent as possible.In the paper,the basic theory and algorithm are briefly introduced,and then the ICA is used for the processing of the data sampled from factory.The results show that ICA has high ability to separate the original source signals from their mixtures,consequently providing an effective technology for the pretreatment of signals to condition monitoring and fault diagnosis of mechanical equipment.