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Enhanced stabilization diagram for automated modal parameter identification based on power spectral density transmissibility functions

Afshar, M ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1002/stc.2369
  3. Publisher: John Wiley and Sons Ltd , 2019
  4. Abstract:
  5. Operational modal analysis based on power spectral density transmissibility (PSDT) functions is a useful tool to identify the modal parameters with low sensitivity to excitations. For pole extraction from the PSDT function, a proper parametric identification method such as the polyreference least squares complex frequency-domain method or poly-Max method can be used. Then, the poles are selected from a stabilization diagram (SD) with overestimating the system model order. Therefore, spurious modes can be identified that must be distinguished and removed from the system poles. To reach this aim, many techniques have been proposed and applied. In this paper, a new algorithm is proposed to enhance the performance of the SD for automated modal parameter identification based on the PSDT. The algorithm is composed of two main phases. In the first phase, the spurious modes are discriminated from the system poles on the basis of the conventional and supplementary stability criteria. On spurious mode omission, two new criteria named “pole criterion” and “coherence criterion” are introduced and applied as the supplementary stability criteria to make a more clear SD. Then, the extracted poles are categorized in the distinct clusters through a new strategy for comparing modes. In the second phase, a novel multiscreening algorithm is implemented for the automated identification of the system poles. Accordingly, the searching and averaging processes are followed between clusters, and the poles are screened to automatically identify the system poles on the basis of the numbers of their repetition in the SD via k-means clustering algorithms. Also, to improve the accuracy of the identification, the Hilbert transform is used in the construction of the PSDT functions. Finally, to validate and demonstrate the efficiency of the proposed method, a computer simulation and an experiential case study are considered. © 2019 John Wiley & Sons, Ltd
  6. Keywords:
  7. Automated operational modal analysis ; Multiscreening algorithm ; Pole criterion ; Power spectral transmissibility functions ; Stabilization diagram ; Automation ; Composite beams and girders ; Frequency domain analysis ; K-means clustering ; Least squares approximations ; Mathematical transformations ; Modal analysis ; Poles ; Power spectral density ; Spectral density ; Stability criteria ; Stabilization ; Automated identification ; Coherence criterion ; Modal parameter identification ; Operational modal analysis ; Parametric identification ; Polyreference least squares complex frequencies ; Stabilization diagrams ; Transmissibility functions ; Parameter estimation
  8. Source: Structural Control and Health Monitoring ; Volume 26, Issue 7 , 2019 ; 15452255 (ISSN)
  9. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/stc.2369