Supervised damage and deterioration detection in building structures using an enhanced autoregressive time-series approach

Gharehbaghi, Vahid Reza and Nguyen, Andy and Farsangi, Ehsan Noroozinejad and Yang, T. Y. (2020) Supervised damage and deterioration detection in building structures using an enhanced autoregressive time-series approach. Journal of Building Engineering, 30:101292. pp. 1-16. ISSN 2352-7102

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Abstract

In this paper, a supervised learning approach is introduced for detecting both damage and deterioration in two building models under ambient and forced vibrations. The coefficients and residuals of autoregressive (AR) time-series models are utilized for extracting features through some statistical indices. Moreover, a novel algorithm called best-uncorrelated features selection (BUFS) is proposed and utilized in order to select the most sensitive and uncorrelated features, which are used as predictors. Accordingly, a common set of predictors capable of detecting both damage and deterioration is established and used in order to form a general pattern of the structural condition. Besides, the BUFS algorithm can also be utilized with other features as well as different types of structures and depicts the most sensitive predictors. The results indicate that the proposed method is capable of detecting damage and deterioration in both models precisely, even in a noisy environment, and the appropriate features are introduced.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 -)
Date Deposited: 23 Nov 2020 05:07
Last Modified: 20 Feb 2021 22:05
Uncontrolled Keywords: Autoregressive (AR) time-series; Damage, and deterioration detection; BUFS algorithm; Supervised learning; Ambient vibration; Forced vibration
Fields of Research (2008): 09 Engineering > 0905 Civil Engineering > 090506 Structural Engineering
Fields of Research (2020): 40 ENGINEERING > 4005 Civil engineering > 400510 Structural engineering
Identification Number or DOI: https://doi.org/10.1016/j.jobe.2020.101292
URI: http://eprints.usq.edu.au/id/eprint/39156

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