Uncertainty Quantification for Eigensystem-Realization-Algorithm, A Class of Subspace System Identification

2011 ◽  
Vol 44 (1) ◽  
pp. 6529-6534 ◽  
Author(s):  
Xuan-Binh Lam ◽  
Laurent Mevel
2020 ◽  
Vol 10 (10) ◽  
pp. 3607
Author(s):  
Hoofar Shokravi ◽  
Hooman Shokravi ◽  
Norhisham Bakhary ◽  
Mahshid Heidarrezaei ◽  
Seyed Saeid Rahimian Koloor ◽  
...  

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.


2020 ◽  
Vol 10 (8) ◽  
pp. 2786 ◽  
Author(s):  
Hoofar Shokravi ◽  
Hooman Shokravi ◽  
Norhisham Bakhary ◽  
Seyed Saeid Rahimian Koloor ◽  
Michal Petrů

Structural health monitoring (SHM) is the main contributor of the future’s smart city to deal with the need for safety, lower maintenance costs, and reliable condition assessment of structures. Among the algorithms used for SHM to identify the system parameters of structures, subspace system identification (SSI) is a reliable method in the time-domain that takes advantages of using extended observability matrices. Considerable numbers of studies have specifically concentrated on practical applications of SSI in recent years. To the best of author’s knowledge, no study has been undertaken to review and investigate the application of SSI in the monitoring of civil engineering structures. This paper aims to review studies that have used the SSI algorithm for the damage identification and modal analysis of structures. The fundamental focus is on data-driven and covariance-driven SSI algorithms. In this review, we consider the subspace algorithm to resolve the problem of a real-world application for SHM. With regard to performance, a comparison between SSI and other methods is provided in order to investigate its advantages and disadvantages. The applied methods of SHM in civil engineering structures are categorized into three classes, from simple one-dimensional (1D) to very complex structures, and the detectability of the SSI for different damage scenarios are reported. Finally, the available software incorporating SSI as their system identification technique are investigated.


2020 ◽  
Vol 357 (17) ◽  
pp. 12904-12937 ◽  
Author(s):  
Amirali Sadeqi ◽  
Shapour Moradi ◽  
Kourosh Heidari Shirazi

2014 ◽  
Vol 501-504 ◽  
pp. 856-860
Author(s):  
Yen Po Wang ◽  
Ming Lian Chang ◽  
Jia Ge Chang

In this study, a scheme integrated with deterministic stochastic subspace system identification and the method of damage localization vector (DLV) is proposed for damage detection of structures based on seismic response data. A series of shaking table tests has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom ends. Both single and multiple damage conditions at various locations have been considered. Full or partial observation conditions have been taken into account in the system identification analysis. It has been shown that local damages (stories) can be identified from global responses of the structure to earthquakes if sufficiently observed.


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