Study on modifications of PLS approach for process monitoring
18th IFAC World Congress; 28 August – 2 September 2011; Milano, Italy
In: IFAC Proceedings Volumes, Vol. 44 (2011), No. 1, pp. 12389 - 12394
2011article/chapter in journalOpen Access
Electrical Engineering and Information TechnologyFaculty of Engineering » Engineering and Information Technology » Automatic Control and Complex Systems
Related: 1 publication(s)
Title in English:
Study on modifications of PLS approach for process monitoring
Conference
18th IFAC World Congress; 28 August – 2 September 2011; Milano, Italy
Author:
Yin, Shen
- GND
- 134302427
- LSF ID
- 2347
- ORCID
-
0000-0002-5149-5918
- Other
- connected with university
- LSF ID
- 52408
- Other
- connected with university
Year of publication:
2011
Open Access?:
Open Access
Scopus ID
Language of text:
English
Appears in
Place of publication:
Amsterdam
Publisher:
Elsevier
in:
Vol. 44 (2011), No. 1, pp. 12389 - 12394
ISSN
ZDB ID
Note:
Bis 47, 2014
Keyword, Topic:
Data-Driven methods ; Fault diagnosis ; Multivariate statistical process monitoring ; Partial least squares ; Tennessee Eastman process
Type of resource:
Text
Abstract in English:
Partial least squares (PLS) is an efficient approach for multivariate statistical process monitoring. Although it works in many industrial applications, Zhou et al. [2010] revealed that some properties of PLS algorithm may hamper overall efficiency of process monitoring scheme. To solve these problems, a modified approach is proposed in this paper. Compared with the existing PLS approaches, the new approach performs an orthogonal decomposition on regression variable space to eliminate the variations useless for output prediction. Based on the new approach, a complete process monitoring scheme is also developed. Finally, the effectiveness of the proposed approach is verified on an industrial benchmark of Tennessee Eastman process.