Deep learning-based detection of structural damage using time-series data
Article
Dang, H.V., Raza, M., Nguyen, T.V., Bui-Tien, T. and Nguyen, H. 2021. Deep learning-based detection of structural damage using time-series data. Structure and Infrastructure Engineering. 17 (11), pp. 1474-1493. https://doi.org/10.1080/15732479.2020.1815225
Type | Article |
---|---|
Title | Deep learning-based detection of structural damage using time-series data |
Authors | Dang, H.V., Raza, M., Nguyen, T.V., Bui-Tien, T. and Nguyen, H. |
Abstract | Previously, it was nearly impossible to use raw time series sensory signals for structural health monitoring due to the inherent high dimensionality of measured data. However, recent developments in deep learning techniques have overcome the need of complex preprocessing in time series data. This study extends the applicability of four prominent deep learning algorithms: Multi-Layer Perceptron, Long Short Term Memory network, 1D Convolutional Neural Network, and Convolutional Neural Network to structural damage detection using raw data. Three structures ranging from relatively small structures to considerably large structures are extensively investigated, i.e., 1D continuous beam under random excitation, a 2D steel frame subjected to earthquake ground motion, and a 3D stayed-cable bridge under vehicular loads. |
Keywords | Vibration; machine learning; finite element methods; signal processing; structural health monitoring; neural network; time-series; structural analysis |
Publisher | Taylor and Francis |
Journal | Structure and Infrastructure Engineering |
ISSN | 1573-2479 |
Electronic | 1744-8980 |
Publication dates | |
Online | 03 Sep 2020 |
02 Nov 2021 | |
Publication process dates | |
Deposited | 22 Jul 2020 |
Accepted | 07 Jul 2020 |
Submitted | 05 Mar 2020 |
Output status | Published |
Digital Object Identifier (DOI) | https://doi.org/10.1080/15732479.2020.1815225 |
Web of Science identifier | WOS:000566625900001 |
Language | English |
https://repository.mdx.ac.uk/item/89049
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