Crack detection in Mindlin-Reissner plates under dynamic loads based on fusion of data and models. (1st April 2021)

• Record Type: Journal Article
• Authors: Agathos, Konstantinos; Tatsis, Konstantinos; Nicoli, Sergio; Bordas, Stéphane P.A.; Chatzi, Eleni
• Is Part Of: Computers & structures. Volume 246(2021)
• Publication Date: 2021-04-01
• Subjects: Crack detection -- Structural health monitoring -- XFEM -- Modal strain curvatures; Structural engineering -- Data processing -- Periodicals; Electronic data processing -- Structures, Theory of -- Periodicals; 624.171
• DOI: 10.1016/j.compstruc.2020.106475
• Languages: English
• ISSNs: 0045-7949

Abstract

Highlights: Crack detection based on XFEM is extended to the case of plates under dynamic loads. System identification is used to provide an initial estimate for the crack location. Modal strain curvatures are used as a damage index. Accurate crack localization is consistently obtained. Abstract: In this paper, system identification is coupled with optimization-based damage detection to provide accurate localization of cracks in thin plates, under dynamic loading. Detection relies on exploitation of strain measurements from a network of sensors deployed onto the plate structure. The data-driven approach is based on the detection of discrepancies between healthy and damaged modal strain curvatures, while the model-based method exploits an enriched finite element method coupled to an optimization algorithm to minimize discrepancies between the measured and modelled response of the structure. It is demonstrated, through a series of numerical experiments, that the fusion of data-driven and model-based approaches can be beneficial both in terms of accuracy and localization, as well as in terms of computational requirements.