POD Curves for Natural Frequency Testing - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2022

POD Curves for Natural Frequency Testing

Résumé

Evaluating natural frequencies for damage detection and localization is a standard procedure in non-destructive testing (NDT) and structural health monitoring (SHM). In particular, for cables and other prestressed tendons, natural frequencies exhibit high sensitivities to structural changes, which is often demonstrated by comparing the frequencies before and after damage occurred, e.g., using probability of detection (POD) or probability of localization (POL) curves. In this paper, an approach is developed to predict POD/POL curves without any data from the damaged state. The method is based on data from the undamaged state and a numerical model, which is utilized to obtain sensitivity vectors that linearize the relation between frequency changes and changes in structural parameters. At the same time, statistical uncertainties in the frequency estimation process are considered. Based on this method, a cable monitoring strategy is suggested, where sensitivity vectors are first used to calibrate decisive cable properties using model updating, followed by a performance assessment through POD/POL curves, and a continuous damage detection and localization based on statistical tests. The synergic effects of the presented methods are demonstrated by means of a numerical case study on a prestressed cable, where data from a single uni-axial vibration sensor is evaluated. The results indicate that changes in stiffness and axial forces can be distinguished using localization tests, but additional sensors and features are necessary for damage localization along the cable.
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Dates et versions

hal-03863131 , version 1 (21-11-2022)

Identifiants

  • HAL Id : hal-03863131 , version 1

Citer

Alexander Mendler, Michael Döhler, Christian U. Grosse. POD Curves for Natural Frequency Testing. NDE 4.0 2022 - International Conference on NDE 4.0, Oct 2022, Berlin, Germany. pp.1-12. ⟨hal-03863131⟩
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