Journal
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
Volume 13, Issue 2, Pages 1129-1137Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TASE.2015.2477272
Keywords
Concurrent kernel projection to latent structures (CKPLS); nonlinear process monitoring; process-relevant fault detection; quality-relevant fault detection
Categories
Funding
- Natural Science Foundation of China [61304107, 61490704, 61573022, 61290323]
- China Postdoctoral Science Foundation [2013M541242]
- International Postdoctoral Exchange Fellowship Program [20130020]
- Fundamental Research Funds for the Central Universities [N130408002, N130108001]
- IAPI Fundamental Research Funds [2013ZCX04, 2013ZCX05]
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Projection to latent structures (PLS) and concurrent PLS are approaches for solving quality-relevant process monitoring. In this paper, a new approach called concurrent kernel PLS (CKPLS) is presented to detect faults comprehensively for nonlinear processes. The new model divides the nonlinear process and quality spaces into five subspaces: the co-varying, process-principal, process-residual, quality-principal, and quality-residual subspaces. The co-varying subspace reflects nonlinear relationship between quality variables and original process variables. The process-principal and process-residual subspaces reflect the principal variations and residuals, respectively, in the nonlinear process space. Further, the quality-principal and quality-residual subspaces reflect the principal variations and residuals, respectively, in the quality space. The proposed approach is demonstrated by a numerical simulation and an application of the Tennessee Eastman process.
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