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Structural Damage Detection in Real Time: Implementation of 1D Convolutional Neural Networks for SHM Applications
Qatar University, Qatar.
Qatar University, Qatar.ORCID iD: 0000-0003-0530-9552
Qatar University, Qatar.
University of Michigan, USA.
2017 (English)In: Structural Health Monitoring & Damage Detection, Volume 7: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics 2017 / [ed] Christopher Niezrecki, Springer, 2017, Vol. 7, p. 49-54Conference paper, Published paper (Other academic)
Abstract [en]

Most of the classical structural damage detection systems involve two processes, feature extraction and feature classification. Usually, the feature extraction process requires large computational effort which prevent the application of the classical methods in real-time structural health monitoring applications. Furthermore, in many cases, the hand-crafted features extracted by the classical methods fail to accurately characterize the acquired signal, resulting in poor classification performance. In an attempt to overcome these issues, this paper presents a novel, fast and accurate structural damage detection and localization system utilizing one dimensional convolutional neural networks (CNNs) arguably for the first time in SHM applications. The proposed method is capable of extracting optimal damage-sensitive features automatically from the raw acceleration signals, allowing it to be used for real-time damage detection. This paper presents the preliminary experiments conducted to verify the proposed CNN-based approach.

Place, publisher, year, edition, pages
Springer, 2017. Vol. 7, p. 49-54
National Category
Other Civil Engineering
Research subject
Technology (byts ev till Engineering), Civil engineering
Identifiers
URN: urn:nbn:se:lnu:diva-89746ISBN: 9783319541082 (print)OAI: oai:DiVA.org:lnu-89746DiVA, id: diva2:1362666
Conference
IMAC, A Conference and Exposition on Structural Dynamics
Available from: 2019-10-21 Created: 2019-10-21 Last updated: 2019-12-17Bibliographically approved

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Abdeljaber, Osama

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  • asciidoc
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