Fault Detection Using Canonical Variate Analysis-Reference-Cited by-同舟云学术

Fault Detection Using Canonical Variate Analysis

Published:2003-12-19 Issue:2 Volume:43 Page:458-474
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Juricek Ben C.¹,Seborg Dale E.¹,Larimore Wallace E.¹

Affiliation:

1. Toyon Research Corporation, 75 Aero Camino, Suite A, Goleta, California 93106, Department of Chemical Engineering, University of California, Santa Barbara, California 93106, and Adaptics, Inc., 1717 Briar Ridge Road, McLean, Virginia 22101

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ie0301684

Reference26 articles.

1. Juricek, B. Multivariable Statistical Methods for System Identification and Process Monitoring. Ph.D. Dissertation, Department of Chemical Engineering, University of California, Santa Barbara, CA, 2002.

2. A review of multivariate control charts

3. Using On-Line Process Data to Improve Quality: Challenges for Statisticians

4. Statistical process control of multivariate processes

Cited by 79 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A fault detection method based on sparse dynamic canonical correlation analysis;The Canadian Journal of Chemical Engineering;2023-11-05

2. Data-driven supply chain monitoring using canonical variate analysis;Computers & Chemical Engineering;2023-06

3. CNN-LSTM-CVA Based Quality Monitoring of Waviness for Float Glass Manufacturing Process;2023 35th Chinese Control and Decision Conference (CCDC);2023-05-20

4. Structured fault information-aided canonical variate analysis model for dynamic process monitoring;Journal of Process Control;2023-04

5. Geometrical analysis of consecutive dynamic behaviors in process monitoring;Journal of Process Control;2023-03