Research Article | OPEN ACCESS
Biological Nitrogen Removal Process Monitoring Based on Fuzzy Robust PCA
1Nabila Heloulou, 1Messaoud Ramdani and 2Abdenabi Abidi
1Department of Electronics
2Department of Engineering, Laboratoire d'Automatique et Signaux de Annaba (LASA),
Universit
Research Journal of Applied Sciences, Engineering and Technology 2014 21:4434-4444
Received: November 26, 2013 | Accepted: January 16, 2014 | Published: June 05, 2014
Abstract
In this study the Fuzzy Robust Principal Component Analysis (FRPCA) method is used to monitor a biological nitrogen removal process, performances of this method are then compared with classical principal component analysis. The obtained results demonstrate the performances superiority of this robust extension compared with the conventional one. In this method fuzzy variant of PCA uses fuzzy membership and diminish the effect of outliers by assigning small membership values to outliers in order to make it robust. For the purpose of fault detection, the SPE index is used. Then the fault localization by contribution plots approach and SVI index are exploited.
Keywords:
Biological nitrogen removal, fault diagnosis, fuzzy robust PCA, multivariate statistical process control, process monitoring, water treatment plant,
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Competing interests
The authors have no competing interests.
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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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