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中文摘要：
作为数据驱动故障检测方法中的重要分支,基于多元统计分析的故障检测方法主要包括主元分析、偏最小二乘、独立元素分析和费舍尔判别分析.本文回顾了上述几种方法,包括数据模型、故障检测的原理及方法优劣.仿真实验说明了几种方法的特性及其故障检测的效果,并探讨了基于数据故障检测方法中的一些问题.
英文摘要：
As an important branch of data-driven fault detection methods, multivariate statistical analysis- based fault detection methods mainly include principal component analysis, partial least squares, independ- ent component analysis and fisher discriminant analysis. In this paper, the data model and fault detection mechanism of each method mentioned above were reviewed. Several properties of these methods were re- vealed intuitively using simulation results, and their fault detection abilities were illustrated. Finally, sev- eral problems related to data-driven fault detection methods were discussed.
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