Online diagnostics of time-varying nonlinear chemical processes using moving window kernel principal component analysis and Fisher discriminant analysis

Author:

Galiaskarov M. R.1,Kurkina V. V.1,Rusinov L. A.1

Affiliation:

1. Saint Petersburg State Institute of Technology (Technical University); Russian Federation

Publisher

Wiley

Subject

Applied Mathematics,Analytical Chemistry

Reference28 articles.

1. Some notes on multivariate statistical process control;Rogalewicz;Management and Production Engineering Review,2012

2. Multivariate statistical process control charts: an overview;Bersimis;Qual Reliab Engng Int,2007

3. Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

4. Evolving kernel principal component analysis for fault diagnosis;Sun;Comput Ind Eng,2007

5. Nonlinear process monitoring using kernel principal component analysis;Lee;Chem Eng Sci,2004

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