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Pearson Correlation and Discrete Wavelet Transform for Crack Identification in Steel Beams

Author

Listed:
  • Morteza Saadatmorad

    (School of Mechanical Engineering, Babol Noshirvani University of Technology, Babol 4714871167, Iran)

  • Ramazan-Ali Jafari Talookolaei

    (School of Mechanical Engineering, Babol Noshirvani University of Technology, Babol 4714871167, Iran)

  • Mohammad-Hadi Pashaei

    (School of Mechanical Engineering, Babol Noshirvani University of Technology, Babol 4714871167, Iran)

  • Samir Khatir

    (Faculty of Civil Engineering, Ho Chi Minh City Open University, Ho Chi Minh City 700000, Vietnam
    Soete Laboratory, Faculty of Engineering and Architecture, Ghent University, Technologiepark Zwijnaarde 903, B-9052 Zwijnaarde, Belgium)

  • Magd Abdel Wahab

    (Soete Laboratory, Faculty of Engineering and Architecture, Ghent University, Technologiepark Zwijnaarde 903, B-9052 Zwijnaarde, Belgium)

Abstract

Discrete wavelet transform is a useful means for crack identification of beam structures. However, its accuracy is severely dependent on the selecting mother wavelet and vanishing moments, which raises a significant challenge in practical structural crack identification. In this paper, a novel approach is introduced for structural health monitoring of beams to fix this challenge. The approach is based on the combination of statistical characteristics of vibrational mode shapes of the beam structures and their discrete wavelet transforms. First, this paper suggests using regression statistics between intact and damaged modes to monitor the health of beam structures. Then, it suggests extracting quasi-Pearson-based mode shape index of the beam structures to use them as an original signal in discrete wavelet transforms. Findings show that the proposed approach has several advantages compared with the conventional mode shape signal processing by the discrete wavelet transforms and significantly improves damage detection’s accuracy.

Suggested Citation

  • Morteza Saadatmorad & Ramazan-Ali Jafari Talookolaei & Mohammad-Hadi Pashaei & Samir Khatir & Magd Abdel Wahab, 2022. "Pearson Correlation and Discrete Wavelet Transform for Crack Identification in Steel Beams," Mathematics, MDPI, vol. 10(15), pages 1-23, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:15:p:2689-:d:875784
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    Citations

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    Cited by:

    1. Frédéric Lebon & Isabelle Ramière, 2023. "Advanced Numerical Methods in Computational Solid Mechanics," Mathematics, MDPI, vol. 11(6), pages 1-3, March.
    2. Jose M. Machorro-Lopez & Jorge A. Hernandez-Figueroa & Francisco J. Carrion-Viramontes & Juan P. Amezquita-Sanchez & Martin Valtierra-Rodriguez & Saul E. Crespo-Sanchez & Jesus J. Yanez-Borjas & Juan , 2023. "Analysis of Acoustic Emission Signals Processed with Wavelet Transform for Structural Damage Detection in Concrete Beams," Mathematics, MDPI, vol. 11(3), pages 1-19, January.

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