Fast uncertainty computation for multi-order subspace-based method with QR decompositions
Corressponding author's email:
binhlx@hcmute.edu.vnKeywords:
Stochastic Subspace Identification, Multi-order, QR Decomposition, Uncertainty Computation, Operational Modal AnalysisAbstract
In Operational Modal Analysis, the Stochastic Subspace Identification (SSI) does not yield the exact system matrices, hence there is uncertainty in the estimates of modal parameters (natural frequencies, damping ratios, mode shapes). From that, it is necessary to evaluate the uncertainty of modal parameters. Recently, a new algorithm (multi-order subspace-based method) for determining modal parameters obtained from SSI has been proposed using QR decomposition (QRD). This new multi-order SSI method will partition the up-shifting observability matrix into smaller matrices, then the new state transition matrix is identified by using these smaller matrices. The article will propose a new algorithm for computing the uncertainty on modal parameters obtained from this multi-order SSI (MOSSI) based on QR decomposition (QRD). The new uncertainty algorithm only computes uncertainty bounds at the highest model order and gives bounds at lower orders by mean of selection matrices.
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