Multi-taper method based substructure identification for shear structures

Quickly and accurately identifying structural status after natural disasters plays crucial roles in disaster rescue. Previously, the authors developed a substructure identification method for shear structures, which uses the frequency responses of short structural acceleration responses to estimate...

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Veröffentlicht in:Journal of vibration and control 2020-08, Vol.26 (15-16), p.1266-1275
Hauptverfasser: Zhang, Dongyu, Huang, Yong, Li, Ruifeng, Li, Hui
Format: Artikel
Sprache:eng
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Zusammenfassung:Quickly and accurately identifying structural status after natural disasters plays crucial roles in disaster rescue. Previously, the authors developed a substructure identification method for shear structures, which uses the frequency responses of short structural acceleration responses to estimate structural parameters inductively. However, the numerical studies found that the method could only provide moderately accurate results. In this paper, a thorough uncertainty analysis is performed to reveal the key factors that influence its identification accuracy. Based on these results, a new substructure method is proposed herein, which utilizes the cross power spectrum densities of structural responses, estimated by the multi-taper method, to formulate substructure identification problems. The error analysis is also conducted for the multi-taper method based method, explaining why this method can significantly improve identification accuracy, compared with the frequency response based method. Moreover, although the multi-taper method based method is originally derived based on stationary structural responses, a further analysis shows that it can be extended to non-stationary responses, greatly broadening the method’s application range. Finally, the simulation study of a 20-story shear structure and the shake table tests on a three-story bench-scaled structure are conducted, which verified that the proposed multi-taper method based method indeed significantly improves the substructure identification accuracy.
ISSN:1077-5463
1741-2986
DOI:10.1177/1077546319895360