Damage detection in structural health monitoring using kernel PLS based GLR

Marwa Chaabane, 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

The objective of this paper is to extend the applicability of the GLR method to a wide range of practical systems. Most real systems are nonlinear, multivariate, and are best represented by input-output type of models. Kernel partial least squares (KPLS) models have been widely used to represent such systems. Therefore, in this paper, kernel PLS-based GLR method will be utilized in practice to improve damage detection in Structural Health Monitoring (SHM). The developed kernel PLS-based GLR technique combines the benefits of the multivariate input-output kernel PLS model and the statistical fault detection GLR statistic which showed performance in the cases where process models are not available. GLR is a well-known statistical detection method that relies on maximizing the detection probability for a given false alarm rate. To calculate the kernel PLS model, we use the data collected from the complex 3DOF spring-mass-dashpot system. The simulation results show improved performance of kernel PLS-based GLR in damage detection compared to the classical kernel PLS method.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017
EditorsAhmed Ben Hamida, Basel Solaiman, Ahmed Ben Slima, Mohammed El Hassouni, Mohammed Karim
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

Publication series

NameProceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017

Other

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

Keywords

  • Damage Detection
  • Generalized Likelihood Ratio
  • Kernel Partial Least Squares
  • Structural Health Monitoring

ASJC Scopus subject areas

  • Signal Processing

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  • Cite this

    Chaabane, M., Mansouri, M., Nounou, H., Nounou, M., Ben Slima, M., & Ben Hamida, A. (2017). Damage detection in structural health monitoring using kernel PLS based GLR. In A. B. Hamida, B. Solaiman, A. B. Slima, M. El Hassouni, & M. Karim (Eds.), Proceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017 [8075555] (Proceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ATSIP.2017.8075555