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Robust Structural Damage Detection Using Analysis of the CMSE Residual’s Sensitivity to Damage
Open AccessReview

Application of the Subspace-Based Methods in Health Monitoring of Civil Structures: A Systematic Review and Meta-Analysis

1
School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
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Department of Civil Engineering, Islamic Azad University, Tabriz 5157944533, Iran
3
Institute of Noise and Vibration, Universiti Teknologi Malaysia, City Campus, Jalan Semarak, Kuala Lumpur 54100, Malaysia
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School of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
5
Institute for Nanomaterials, Advanced Technologies and Innovation (CXI), Technical University of Liberec (TUL), Studentska 2, 461 17 Liberec, Czech Republic
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(10), 3607; https://doi.org/10.3390/app10103607
Received: 21 April 2020 / Revised: 11 May 2020 / Accepted: 15 May 2020 / Published: 22 May 2020
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
A large number of research studies in structural health monitoring (SHM) have presented, extended, and used subspace system identification. However, there is a lack of research on systematic literature reviews and surveys of studies in this field. Therefore, the current study is undertaken to systematically review the literature published on the development and application of subspace system identification methods. In this regard, major databases in SHM, including Scopus, Google Scholar, and Web of Science, have been selected and preferred reporting items for systematic reviews and meta-analyses (PRISMA) has been applied to ensure complete and transparent reporting of systematic reviews. Along this line, the presented review addresses the available studies that employed subspace-based techniques in the vibration-based damage detection (VDD) of civil structures. The selected papers in this review were categorized into authors, publication year, name of journal, applied techniques, research objectives, research gap, proposed solutions and models, and findings. This study can assist practitioners and academicians for better condition assessment of structures and to gain insight into the literature. View Full-Text
Keywords: subspace system identification; data-driven stochastic subspace identification (SSI-DATA); covariance-driven stochastic subspace identification (SSI-COV); combined subspace system identification; PRISMA; damage detection; vibration-based damage detection subspace system identification; data-driven stochastic subspace identification (SSI-DATA); covariance-driven stochastic subspace identification (SSI-COV); combined subspace system identification; PRISMA; damage detection; vibration-based damage detection
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Shokravi, H.; Shokravi, H.; Bakhary, N.; Heidarrezaei, M.; Rahimian Koloor, S.S.; Petrů, M. Application of the Subspace-Based Methods in Health Monitoring of Civil Structures: A Systematic Review and Meta-Analysis. Appl. Sci. 2020, 10, 3607.

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