Issue |
MATEC Web Conf.
Volume 349, 2021
6th International Conference of Engineering Against Failure (ICEAF-VI 2021)
|
|
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Article Number | 03012 | |
Number of page(s) | 8 | |
Section | Components and Structural Elements in Engineering Applications: Design, Detections of Defects, Structural Health Monitoring | |
DOI | https://doi.org/10.1051/matecconf/202134903012 | |
Published online | 15 November 2021 |
Model-Based Structural Health Monitoring of Box Girders
Shipbuilding Technology Laboratory, School of Naval Architecture and Marine Engineering, National Technical University of Athens, 106 82, Athens, Greece
* Corresponding author: kanyf@naval.ntua.gr
In the recent years, interest has been expressed towards incorporating Structural Health Monitoring (SHM) systems to ship hulls in order to transition from preventive to predictive maintenance procedures. In this work, an initial approach is undertaken to investigate the capabilities of a model-based method treating damage identification as an optimization problem solved using a genetic algorithm. An idealization of the hull structure is considered based on hull girder theory that allows for lab scale experimental testing. Specifically, a box girder is considered with a circular discontinuity as the generalized damage that causes extensive stress redistribution, replicating the effect of hull damage modes of interest. A three-point bending load case is considered to emulate still water bending loads. Damage is considered to exist, and the goal of the proposed strategy is to provide a prediction on its location and magnitude (level 2 SHM). This is achieved using strain measurements obtained from sensors located on theoretical zero-strain directions as inputs to the optimization scheme treating the damage identification problem. Results from both assessment strategies highlighted the influence of measurement-related uncertainties on the method’s predictive capabilities.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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