An Overview of Conventional MSPC Methods

The MSPC-based method is the main data-driven fault monitoring and diagnosis method, which takes principal component analysis (PCA)(Word et al. in Chemom Intell Lab Syst 2:37–52, 1987), partial least squares (PLS) (Burnham et al. in J Chemom 10:31–45, 1996;De in Chemom Intell Lab Syst 18:251–263, 1993;), Fisher discriminant analysis (FDA)( Chiang LH, Kotanchek ME, Kordon AK (2004) Fault diagnosis based on fisher discriminant analysis and support vector machines. Comput Chem Eng 28(8):1389–1401), independent component analysis (ICA) (Hyvärinen and Oja in Neural Netw 13:411–430, 2000), etc. as the core. This chapter will briefly introduce the main principle of the above-mentioned models and some MSPC-based process monitoring and diagnosis methods.