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Non-Destructive Damage Detection of Structural Joint by Coaxial Correlation Method in 6D Space

Auteur(s): ORCID

ORCID
Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 5, v. 13
Page(s): 1151
DOI: 10.3390/buildings13051151
Abstrait:

Failure of joints can lead to structural collapse. It is vital to monitor joint stiffness during operation to prevent such failures. This paper proposes a novel method for the quality assessment of structural joints using coaxial correlation in 6D space. Coaxially placed 6D sensors on either side of the joint implemented by 3D accelerometers and 3D gyroscopes with wide frequency range, automatic synchronisation between the input signal and receivers and response signal averaging are presented. The root mean square (RMS) value from the obtained signals convolution is proposed as a measure of the similarity between two signals for monitoring joint degradation. The method’s effectiveness was tested on steel beam splice connection, where it was found that the RMS of convolution signals in 6D space showed a direct correlation between the calculated RMS value in X, Y, GX, and GY axes directions and the stiffness grades of the joint. The paper concludes that the nature of the RMS during the degradation of the joint may change in different axes, and wrongly chosen axes may lead to wrong conclusions regarding the state of the investigated joint, especially in the case of complex joints, so that the measurements in 6D provide higher reliability of the result interpretation.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10728057
  • Publié(e) le:
    30.05.2023
  • Modifié(e) le:
    01.06.2023
 
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