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Structural health monitoring of VBI systems via signal processing of vibration data

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thesis
posted on 2023-05-28, 01:09 authored by Mousavi, M
This thesis presents a collection of innovative signal processing strategies to detect both location and severity of damage in bridge structures using moving mass experiments. The literature reviewed shows that parametric damage detection strategies require different types of information from the both intact and damaged structures, such as (1) a finite element model (FEM) of the intact structure, (2) data collected from the intact structure, or (3) data collected only from the damaged structure. Methods are proposed that exploit one or more of the aforementioned information types. These methods are tested using numerical Vehicle Bridge Interaction (VBI) models that consider the effect of road roughness, measurement noise and boundary conditions through Monte Carlo simulation. Analytical formulas are derived to calculate damage severity using data obtained from VBI models. The proposed methods are proven to be robust to as much as 100% noise in measurements and their superiority over other state-of-the-art methods from the literature is demonstrated. In particular it is noted that in most methods reported in the literature a constant moving load velocity is assumed, while the present work demonstrates the ability to locate and quantify the damage with a moving load of variable velocity. Finally, state-of-the-art real-time damage detection may use advanced sensing technologies. It is shown how a new piezo-floating-gate (PFG) sensor may be used in a damage detection strategy that outperforms other techniques proposed in the literature

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  • Unpublished

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Copyright 2020 the author Chapter 2.2 appears to be the equivalent of a post-print version of an article published as: Mousavi, M., Holloway, D., Olivier, J. C., 2019. Using a moving load to simultaneously detect location and severity of damage in a simply supported beam, Journal of vibration and control, 25(15), 2108-2123. Copyright the author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). Chapter 2.3 appears to be the equivalent of a pre-print version of an article published as: Mousavi, M., Holloway, D., Olivier, J. C., Gandomi, A. H., 2021. A baseline-free damage detection method using VBI incomplete, Measurement, 174, 1-16 Chapter 3.2 appears to be the equivalent of a post-print version of an article published as: Mousavi, M., Holloway, D., Olivier, J. C., 2020. A new signal reconstruction for damage detection on a simply supported beam subjected to a moving mass, Journal of civil structural health monitoring, 10, 709-728 Chapter 3.4 appears to be the equivalent of a post-print version of an article published as: Mousavi, M., Holloway, D., Olivier, J. C., Gandomi, A. H., 2020. A spline method based on the crack induced deflection for bridge damage detection, Advances in engineering software, 149, 102894 Chapter 4.2 appears to be the equivalent of a post-print version of an article published as: Mousavi, M., Holloway, D., Olivier, J. C., Alavi, A. H., Gandomi, A. H., 2019. A Shannon entropy approach for structural damage identification based on self-powered sensor data, Engineering structures, 200, 109619

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