Abstract
One of the main tasks in structural health monitoring process is to create reliable algorithms that are capable of translating the measured response into meaningful information reflecting the actual condition of the monitored structure. The authors have recently introduced a novel unsupervised vibration-based damage detection algorithm that utilizes self-organizing maps to quantify structural damage and assess the overall condition of structures. Previously, this algorithm had been tested using the experimental data of Phase II Experimental Benchmark Problem of Structural Health Monitoring, introduced by the IASC (International Association for Structural Control) and ASCE (American Society of Civil Engineers). In this paper, the ability of this algorithm to quantify structural damage is tested analytically using an experimentally validated finite element model of a laboratory structure constructed at Qatar University.
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Acknowledgements
The financial support for this research was provided by Qatar National Research Fund, QNRF (a member of Qatar Foundation) via the National Priorities Research Program (NPRP), Project Number: NPRP 6-526-2-218. The statements made herein are solely the responsibility of the authors.
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© 2016 The Society for Experimental Mechanics, Inc.
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Abdeljaber, O., Avci, O., Do, N.T., Gul, M., Celik, O., Catbas, F.N. (2016). Quantification of Structural Damage with Self-Organizing Maps. In: Wicks, A., Niezrecki, C. (eds) Structural Health Monitoring, Damage Detection & Mechatronics, Volume 7. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-29956-3_5
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DOI: https://doi.org/10.1007/978-3-319-29956-3_5
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