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Contribution rate plot for nonlinear quality-related fault diagnosis with application to the hot strip mill process

  • Published:2013-04 Issue:4 Volume:21 Page:360-369
  • ISSN:0967-0661
  • Container-title:Control Engineering Practice
  • language:en
  • Short-container-title:Control Engineering Practice

Author:

Peng Kaixiang,Zhang Kai,Li Gang,Zhou Donghua

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference40 articles.

1. Alcala, C. F., & Qin, S. J. (2010). Reconstruction-based contribution for process monitoring with kernel principal component analysis. In American control conference (pp. 7022–7027).

2. Analysis and generalization of fault diagnosis methods for process monitoring;Alcala;Journal of Process Control,2011

3. Non-linear projection to latent structures revisited (the quadratic PLS algorithm);Baffi;Computer and Chemical Engineering,1999

4. Non-linear projection to latent structures revisited (the neural network PLS algorithm);Baffi;Computer and Chemical Engineering,1999

5. Non-linear dynamic projection to latent structures modeling;Baffif;Chemometrics and Intelligent Laboratory Systems,2000
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