Damage detection using enhanced multivariate statistical process control technique

Marwa Chaabane, Ahmed Ben Hamida, Majdi Mansouri, Hazem Nounou, Onur Avci

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

5 Citations (Scopus)

Abstract

This paper addresses the problem of damage detection technique of structural health monitoring (SHM). Kernel principal components analysis (KPCA)-based generalized likelihood ratio (GLR) technique is developed to enhance the damage detection of SHM processes. The data are collected from the complex three degree of freedom spring-mass-dashpot system in order to calculate the KPCA model. The developed KPCA-based GLR is the method that attempts to combine the advantages of GLR statistic in the cases where process models are not available and a multivariate statistical process control; KPCA. The simulations show the improved performance of the KPCA-based GLR damage detection method.

Original languageEnglish
Title of host publication2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages234-238
Number of pages5
ISBN (Electronic)9781509034079
DOIs
Publication statusPublished - 16 Jun 2017
Event17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Sousse, Tunisia
Duration: 19 Dec 201621 Dec 2016

Other

Other17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016
CountryTunisia
CitySousse
Period19/12/1621/12/16

Fingerprint

Multivariate Statistical Process Control
Kernel Principal Component Analysis
Statistical process control
Damage Detection
Damage detection
principal components analysis
likelihood ratio
Principal component analysis
damage
Likelihood Ratio
structural health monitoring
Structural health monitoring
Health Monitoring
Likelihood Ratio Statistic
Process Model
degrees of freedom
Degree of freedom
Statistics
statistics
Calculate

Keywords

  • Damage detection
  • GLR
  • Kernel PCA
  • SHM

ASJC Scopus subject areas

  • Hardware and Architecture
  • Automotive Engineering
  • Control and Optimization
  • Instrumentation
  • Artificial Intelligence

Cite this

Chaabane, M., Ben Hamida, A., Mansouri, M., Nounou, H., & Avci, O. (2017). Damage detection using enhanced multivariate statistical process control technique. In 2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings (pp. 234-238). [7952052] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/STA.2016.7952052

Damage detection using enhanced multivariate statistical process control technique. / Chaabane, Marwa; Ben Hamida, Ahmed; Mansouri, Majdi; Nounou, Hazem; Avci, Onur.

2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 234-238 7952052.

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

Chaabane, M, Ben Hamida, A, Mansouri, M, Nounou, H & Avci, O 2017, Damage detection using enhanced multivariate statistical process control technique. in 2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings., 7952052, Institute of Electrical and Electronics Engineers Inc., pp. 234-238, 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016, Sousse, Tunisia, 19/12/16. https://doi.org/10.1109/STA.2016.7952052
Chaabane M, Ben Hamida A, Mansouri M, Nounou H, Avci O. Damage detection using enhanced multivariate statistical process control technique. In 2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 234-238. 7952052 https://doi.org/10.1109/STA.2016.7952052
Chaabane, Marwa ; Ben Hamida, Ahmed ; Mansouri, Majdi ; Nounou, Hazem ; Avci, Onur. / Damage detection using enhanced multivariate statistical process control technique. 2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 234-238
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