Application of Couple Sparse Coding in Smart Damage Detection of Truss Bridges

Fallahian, Milad and Ahmadi, Ehsan and Talaei, Saeid and Kashani, Mohammad M. (2022) Application of Couple Sparse Coding in Smart Damage Detection of Truss Bridges. Proceedings of the ICE - Bridge Engineering. ISSN 1478-4637

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Abstract

Damage detection of bridge structures plays a crucial role in in-time maintenance of such structures, which subsequently prevents further propagation of the damage, and likely collapse of the structure. Currently, the application of machine learning algorithms are growing in smart damage detection of structures. This work focuses on application of a new machine learning algorithm to identify the location and severity of damage in truss bridges. Frequency Response Functions (FRFs) are used as damage features, and are compressed using Principal Component Analysis (PCA). Couple Sparse Coding (CSC) is adopted as a classification method to learn the relationship between the bridge damage features and its damage states. Two truss bridges are used to test the proposed method and determine its accuracy in damage detection of truss bridges. It is found that the proposed method provides a reliable detection of damage location and severity in truss bridges.

Item Type:	Article
Identification Number:	10.1680/jbren.22.00017
Dates:	Date Event 17 August 2022 Accepted 25 August 2022 Published Online
Uncontrolled Keywords:	Smart Damage Detection Frequency Response Function (FRF) Principal Component Analysis (PCA) Couple Sparse Coding (CSC) Truss Bridges
Subjects:	CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-01 - engineering (non-specific)
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Built Environment
Depositing User:	Ehsan Ahmadi
Date Deposited:	31 Aug 2022 10:43
Last Modified:	20 Jun 2024 11:45
URI:	https://www.open-access.bcu.ac.uk/id/eprint/13500

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