Validation of a procedure for the evaluation of the performance of an installed structural health monitoring system
Auteur(s): |
Sebastian Heinlein
Peter Cawley Thomas Vogt |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Structural Health Monitoring, septembre 2018, n. 5-6, v. 18 |
Page(s): | 1557-1568 |
DOI: | 10.1177/1475921718798567 |
Abstrait: |
Validation of the performance of guided wave structural health monitoring systems is vital if they are to be widely deployed; testing the damage detection ability of a system by introducing different types of damage at varying locations is very costly and cannot be performed on a system in operation. Estimating the damage detection ability of a system solely by numerical simulations is not possible as complex environmental effects cannot be accounted for. In this study, a methodology was tested and verified that uses finite element simulations to superimpose defect signals onto measurements collected from a defect-free structure. These signals are acquired from the structure of interest under varying environmental and operational conditions for an initial monitoring period. Measurements collected in a previous blind trial of an L-shaped pipe section, onto which a number of corrosion-like defects were introduced, were utilised during this investigation. The growth of three of these defects was replicated using finite element analysis and the simulated reflections were superimposed onto signals collected on the defect-free test pipe. The signal changes and limits of reliable detection predicted from the synthetic defect reflections superimposed on the measurements from the undamaged complex structure agreed well with the changes due to real damage measured on the same structure. This methodology is of great value for any structural health monitoring system as it allows for the minimum detectable defect size to be estimated for specific geometries and damage locations in a quick and efficient manner without the need for multiple test structures while accounting for environmental variations. |
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10562204 - Publié(e) le:
11.02.2021 - Modifié(e) le:
19.02.2021