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Two-stage automated operational modal analysis based on power spectrum density transmissibility and support-vector machines
Chen, Zhi Wei1; Liu, Kui Ming1; Yan, Wang Ji2; Zhang, Jian Lin1; Ren, Wei Xin3
2021-05-01
Source PublicationInternational Journal of Structural Stability and Dynamics
ISSN0219-4554
Volume21Issue:5Pages:2150068
Abstract

Power spectrum density transmissibility (PSDT) functions have attracted widespread attention in operational modal analysis (OMA) because of their robustness to excitations. However, the selection of the peaks and stability axes are still subjective and requires further investigation. To this end, this study took advantage of PSDT functions and support-vector machines (SVMs) to propose a two-stage automated modal identification method. In the first stage, the automated identification of peaks is achieved by introducing the peak slope (PS) as a critical index and determining its threshold using the SVM classifier. In the second stage, the automated identification of the stability axis is achieved by introducing the relative difference coefficients (RDCs) of the modal parameters as indicators and determining their thresholds using the SVM classifier. To verify its feasibility and accuracy, the proposed method was applied to an ASCE-benchmark structure in the laboratory and in a high-rise building installed with a structural health monitoring system (SHMS). The results showed that the automated identification method could effectively eliminate spurious modes and accurately identify the closely spaced modes. The proposed method can be automatically applied without manual intervention, and it is robust to noise. It is promising for application to the real-Time condition evaluation of civil structures installed with SHMSs.

KeywordMachine Learning Modal Identification Power Spectrum Density Structural Health Monitoring Transmissibility
DOI10.1142/S0219455421500681
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering ; Mechanics
WOS SubjectEngineering, Civil ; Engineering, Mechanical ; Mechanics
WOS IDWOS:000648560200014
PublisherWORLD SCIENTIFIC PUBL CO PTE LTD5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE
Scopus ID2-s2.0-85101761151
Fulltext Access
FWCI0.75973797
Citation statistics
Document TypeJournal article
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding AuthorChen, Zhi Wei
Affiliation1.Department of Civil Engineering, Xiamen University, Xiamen, China
2.State Key Lab. of Internet of Things for Smart City and Dept. of Civil and Environmental Engineering, University of Macau, Macao
3.Department of Civil Engineering, Shenzhen University, China
Recommended Citation
GB/T 7714
Chen, Zhi Wei,Liu, Kui Ming,Yan, Wang Ji,et al. Two-stage automated operational modal analysis based on power spectrum density transmissibility and support-vector machines[J]. International Journal of Structural Stability and Dynamics,2021,21(5):2150068.
APA Chen, Zhi Wei,Liu, Kui Ming,Yan, Wang Ji,Zhang, Jian Lin,&Ren, Wei Xin.(2021).Two-stage automated operational modal analysis based on power spectrum density transmissibility and support-vector machines.International Journal of Structural Stability and Dynamics,21(5),2150068.
MLA Chen, Zhi Wei,et al."Two-stage automated operational modal analysis based on power spectrum density transmissibility and support-vector machines".International Journal of Structural Stability and Dynamics 21.5(2021):2150068.
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