Influence of scaling and unfolding in PCA based monitoring of nutrient removing batch process

Magda Ruiz; Kris Villez; Gurkan Sin; Joan Colomer; Peter Vanrrolleghem

doi:10.3182/20060829-4-cn-2909.00018

Influence of scaling and unfolding in PCA based monitoring of nutrient removing batch process

Magda Ruiz, Kris Villez, Gurkan Sin, Joan Colomer, Peter Vanrrolleghem

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

The data set of batch biological and biotechnological processes can be organized in a three-way data matrix. In this paper the usefulness of different PCA approaches for monitoring is analyzed. Different ways of unfolding and scaling of data have been applied to a pilot-scale SBR data. PCA is used to reduce the dimensionality and to remove the non-linearity dynamic of the data. Moreover, a new method to select the number of principal components is proposed. Loadings graphics are used to determinate the predominant variables for each one. The results show that whatever model can be applied depending on the goal of the monitoring, however the models implicate possible false alarms or faults omission.

Original language	English
Title of host publication	6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006
Publisher	IFAC Secretariat
Pages	114-119
Number of pages	6
Edition	PART 1
ISBN (Print)	9783902661142
DOIs	https://doi.org/10.3182/20060829-4-cn-2909.00018
State	Published - 2006
Externally published	Yes

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Number	PART 1
Volume	6
ISSN (Print)	1474-6670

Funding

This work is part of the project “Development of a intelligent control system apply to a Sequencing Batch Reactor by loads (SBR) for the elimination of organic matter, nitrogen and phosphorus” DPI2005-08922-C02-02 supported by the Spanish Government, the FEDER Founds and the Institute for Encouragement of Innovation by means of Science and Technology in Flanders (IWT).

Keywords

Biological process
Multiway Principal Component Analysis (MPCA)
Process monitoring

Access to Document

10.3182/20060829-4-cn-2909.00018

Cite this

Ruiz, M., Villez, K., Sin, G., Colomer, J., & Vanrrolleghem, P. (2006). Influence of scaling and unfolding in PCA based monitoring of nutrient removing batch process. In 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006 (PART 1 ed., pp. 114-119). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 6, No. PART 1). IFAC Secretariat. https://doi.org/10.3182/20060829-4-cn-2909.00018

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Ruiz, M, Villez, K, Sin, G, Colomer, J & Vanrrolleghem, P 2006, Influence of scaling and unfolding in PCA based monitoring of nutrient removing batch process. in 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006. PART 1 edn, IFAC Proceedings Volumes (IFAC-PapersOnline), no. PART 1, vol. 6, IFAC Secretariat, pp. 114-119. https://doi.org/10.3182/20060829-4-cn-2909.00018

Influence of scaling and unfolding in PCA based monitoring of nutrient removing batch process. / Ruiz, Magda; Villez, Kris; Sin, Gurkan et al.
6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006. PART 1. ed. IFAC Secretariat, 2006. p. 114-119 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 6, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The data set of batch biological and biotechnological processes can be organized in a three-way data matrix. In this paper the usefulness of different PCA approaches for monitoring is analyzed. Different ways of unfolding and scaling of data have been applied to a pilot-scale SBR data. PCA is used to reduce the dimensionality and to remove the non-linearity dynamic of the data. Moreover, a new method to select the number of principal components is proposed. Loadings graphics are used to determinate the predominant variables for each one. The results show that whatever model can be applied depending on the goal of the monitoring, however the models implicate possible false alarms or faults omission.

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Ruiz M, Villez K, Sin G, Colomer J, Vanrrolleghem P. Influence of scaling and unfolding in PCA based monitoring of nutrient removing batch process. In 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006. PART 1 ed. IFAC Secretariat. 2006. p. 114-119. (IFAC Proceedings Volumes (IFAC-PapersOnline); PART 1). doi: 10.3182/20060829-4-cn-2909.00018

Influence of scaling and unfolding in PCA based monitoring of nutrient removing batch process

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