Fault detection of chemical processes using KPCA-based GLRT technique

Raoudha Baklouti, Majdi Mansouri, Hazem Nounou, Mohamed Nounou, Mohamed Ben Slima, Ahmed Ben Hamida

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we address the problem of nonlinear fault detection of chemical processes. The objective is to extend our previous work [1] to provide a better performance in terms of fault detection accuracies by developing a pre-image kernel PCA (KPCA)-based Generalized Likelihood Ratio Test (GLRT) technique. The benefit of the pre-image kPCA technique lies in its ability to compute the residual in the original space using the KPCA from the feature space. In addition, GLRT provides more accurate results in terms of fault detection. The performance of the developed pre-image KPCA-based GLRT fault detection technique is evaluated using simulated continuously stirred tank reactor (CSTR) model.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538605516
DOIs
Publication statusPublished - 19 Oct 2017
Event3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017 - Fez, Morocco
Duration: 22 May 201724 May 2017

Other

Other3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017
CountryMorocco
CityFez
Period22/5/1724/5/17

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Keywords

  • CSTR process
  • Fault Detection
  • Generalized Likelihood Ratio Test
  • Pre-image Kernel
  • Principal Component Analysis

ASJC Scopus subject areas

  • Signal Processing

Cite this

Baklouti, R., Mansouri, M., Nounou, H., Nounou, M., Ben Slima, M., & Ben Hamida, A. (2017). Fault detection of chemical processes using KPCA-based GLRT technique. In Proceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017 [8075513] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ATSIP.2017.8075513