Dynamic concurrent kernel CCA for strip-thickness relevant fault diagnosis of continuous annealing processes-Reference-Cited by-同舟云学术

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Dynamic concurrent kernel CCA for strip-thickness relevant fault diagnosis of continuous annealing processes

Published:2018-07 Issue: Volume:67 Page:12-22
ISSN:0959-1524
Container-title:Journal of Process Control
language:en
Short-container-title:Journal of Process Control

Author:

Liu Qiang,Zhu Qinqin^ORCID,Qin S. Joe,Chai Tianyou

Funder

Natural Science Foundation of China

China Postdoctoral Science Foundation

International Postdoctoral Exchange Fellowship Program

Fundamental Disciplinary Research Program of the Shenzhen Committee on Science and Innovation

Texas–Wisconsin–California Control Consortium

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Modeling and Simulation,Control and Systems Engineering

Reference31 articles.

1. Process data analytics in the era of big data;Qin;AIChE J.,2014

2. Fault diagnosis of continuous annealing processes using a reconstruction-based method;Liu;Control Eng. Pract.,2012

3. Decentralized fault diagnosis of large-scale processes using multiblock kernel partial least squares;Zhang;IEEE Trans. Ind. Inform.,2010

4. Decentralized fault diagnosis of large-scale processes using multiblock kernel principal component analysis;Zhang;Acta Autom. Sinica,2010

5. Decentralized fault diagnosis of continuous annealing processes based on multi-level PCA;Liu;IEEE Trans. Autom. Sci. Eng.,2013

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