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Real-time vibration...
Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks
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- Abdeljaber, Osama (author)
- Qatar University, Qatar
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- Avci, Onur (author)
- Qatar University, Qatar
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- Kiranyaz, Serkan (author)
- Qatar University, Qatar
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- Gabbouj, Moncef (author)
- Tampere University of Technology, Finland
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- Inman, Daniel (author)
- University of Michigan, USA
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(creator_code:org_t)
- Elsevier, 2017
- 2017
- English.
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In: Journal of Sound and Vibration. - : Elsevier. - 0022-460X .- 1095-8568. ; 388, s. 154-170
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has always been one of the principal objectives of SHM applications. The performance of a classical damage detection system predominantly depends on the choice of the features and the classifier. While the fixed and hand-crafted features may either be a sub-optimal choice for a particular structure or fail to achieve the same level of performance on another structure, they usually require a large computation power which may hinder their usage for real-time structural damage detection. This paper presents a novel, fast and accurate structural damage detection system using 1D Convolutional Neural Networks (CNNs) that has an inherent adaptive design to fuse both feature extraction and classification blocks into a single and compact learning body. The proposed method performs vibration-based damage detection and localization of the damage in real-time. The advantage of this approach is its ability to extract optimal damage-sensitive features automatically from the raw acceleration signals. Large-scale experiments conducted on a grandstand simulator revealed an outstanding performance and verified the computational efficiency of the proposed real-time damage detection method.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Annan samhällsbyggnadsteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Other Civil Engineering (hsv//eng)
Keyword
- Byggteknik
- Civil engineering
Publication and Content Type
- ref (subject category)
- art (subject category)
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