2009
DOI: 10.1117/12.815422
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Recursive stochastic subspace identification for structural parameter estimation

Abstract: Identification of structural parameters under ambient condition is an important research topic for structural health monitoring and damage identification. This problem is especially challenging in practice as these structural parameters could vary with time under severe excitation. Among the techniques developed for this problem, the stochastic subspace identification (SSI) is a popular time-domain method. The SSI can perform parametric identification for systems with multiple outputs which cannot be easily do… Show more

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Cited by 8 publications
(7 citation statements)
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“…is paper differs from other papers in the literature of structural health monitoring in several points [1][2][3][4][5][6][7][8][9][10][11][12] and references therein. In the first place, the nonlinear and coupling effects of the railroad segment require the use of high-order models, and if low uncertainty is desired, that has a direct impact on the complexity of the calculations and therefore in the feasibility of real-time implementation of structural health monitoring systems.…”
Section: Introductionmentioning
confidence: 83%
See 1 more Smart Citation
“…is paper differs from other papers in the literature of structural health monitoring in several points [1][2][3][4][5][6][7][8][9][10][11][12] and references therein. In the first place, the nonlinear and coupling effects of the railroad segment require the use of high-order models, and if low uncertainty is desired, that has a direct impact on the complexity of the calculations and therefore in the feasibility of real-time implementation of structural health monitoring systems.…”
Section: Introductionmentioning
confidence: 83%
“…Ambient noise information or structure earthquake response is used in some methods to get modal properties [1][2][3]. Recently, identification methods based on subspaces, as those reported in [4][5][6], have been used in determining and monitoring modal properties in both buildings [7,8] and bridges [9,10]. A review and comparison with classical identification methods can be found in [11,12].…”
Section: Introductionmentioning
confidence: 99%
“…For on‐line identification, the main obstacle of RSI is computation time in using SVD and LQ decomposition. Several RSI algorithms have been proposed to avoid the use of SVD . The basic idea of these algorithms is to use the relationship between the subspace identification and the signal processing problem.…”
Section: Methods Of System Identificationmentioning
confidence: 99%
“…Email: {me2533, dano}@columbia.edu Michael Chertkov is with Los Alamos National Laboratory, Los Alamos, NM and Skolkovo Institute of Science and Technology, Russia. Email: chertkov@lanl.gov analysis of memory effects [18], and linear model driven spectral analysis of the dynamic state matrix [5], [6], [10], [11], [12], [19], [20], [21] are arguably the most popular data-driven techniques currently in use in the power system research.…”
Section: Introductionmentioning
confidence: 99%
“…aforementioned) power system applications. Principal component analysis [13]- [17], auto-correlation analysis of memory effects [18], and linear model driven spectral analysis of the dynamic state matrix [5], [6], [10], [11], [12], [19], [20], [21] are arguably the most popular data-driven techniques currently in use in the power system research.…”
Section: Introductionmentioning
confidence: 99%