Asymptotic identification uncertainty of well-separated modes in operational modal analysis with multiple setups
Operational modal analysis (OMA) aims at identifying structural modal properties with (output-only) ambient vibration data. In the absence of loading information, the identification (ID) uncertainty of modal properties becomes a valid concern in quality control and test planning. One recent developm...
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| 格式: | Journal Article |
| 語言: | English |
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2020
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/145070 |
| _version_ | 1826127339113676800 |
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| author | Xie, Yan-Long Au, Siu-Kui Li, Binbin |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Xie, Yan-Long Au, Siu-Kui Li, Binbin |
| author_sort | Xie, Yan-Long |
| collection | NTU |
| description | Operational modal analysis (OMA) aims at identifying structural modal properties with (output-only) ambient vibration data. In the absence of loading information, the identification (ID) uncertainty of modal properties becomes a valid concern in quality control and test planning. One recent development that addresses this aspect is ‘uncertainty law’, which aims at understanding how ID uncertainty depends on test configuration. Mathematically, uncertainty laws in OMA are asymptotic expressions for the ‘posterior’ (i.e., given data) variance of modal parameters. Analogous to the laws of large numbers in statistics, they are often derived assuming long data, small damping, and high signal-to-noise ratio. Following a Bayesian approach, this work develops the uncertainty law for OMA with multiple setup data, a common strategy to produce a ‘global’ mode shape covering a large number of locations with a small number of sensors in individual setups. It advances over previous results for single setup data, and is motivated by questions, e.g., how does the quality of global mode shape depend on sensor locations and setup schedule? Focusing on the case of fixed reference and distinct rovers, analytical study of the eigenvalue properties of mode shape covariance matrix reveals characteristic spatial patterns where principal uncertainty takes place, which can be of local or global nature. The theory is validated with synthetic, laboratory and field test data. By virtue of the Cramer-Rao bound, up to the same modeling assumptions, the uncertainty law dictates the achievable precision limit of OMA regardless of identification method. |
| first_indexed | 2024-10-01T07:06:57Z |
| format | Journal Article |
| id | ntu-10356/145070 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:06:57Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1450702020-12-10T02:40:23Z Asymptotic identification uncertainty of well-separated modes in operational modal analysis with multiple setups Xie, Yan-Long Au, Siu-Kui Li, Binbin School of Civil and Environmental Engineering Institute of Catastrophe Risk Management (ICRM) Engineering::Civil engineering BAYOMA Cramer-Rao Bound Operational modal analysis (OMA) aims at identifying structural modal properties with (output-only) ambient vibration data. In the absence of loading information, the identification (ID) uncertainty of modal properties becomes a valid concern in quality control and test planning. One recent development that addresses this aspect is ‘uncertainty law’, which aims at understanding how ID uncertainty depends on test configuration. Mathematically, uncertainty laws in OMA are asymptotic expressions for the ‘posterior’ (i.e., given data) variance of modal parameters. Analogous to the laws of large numbers in statistics, they are often derived assuming long data, small damping, and high signal-to-noise ratio. Following a Bayesian approach, this work develops the uncertainty law for OMA with multiple setup data, a common strategy to produce a ‘global’ mode shape covering a large number of locations with a small number of sensors in individual setups. It advances over previous results for single setup data, and is motivated by questions, e.g., how does the quality of global mode shape depend on sensor locations and setup schedule? Focusing on the case of fixed reference and distinct rovers, analytical study of the eigenvalue properties of mode shape covariance matrix reveals characteristic spatial patterns where principal uncertainty takes place, which can be of local or global nature. The theory is validated with synthetic, laboratory and field test data. By virtue of the Cramer-Rao bound, up to the same modeling assumptions, the uncertainty law dictates the achievable precision limit of OMA regardless of identification method. Accepted version This work is part of a research project on ‘‘Uncertainty quantification and management in ambient modal identification” funded by the Engineering and Physical Sciences Research Council, UK (grant EP/N017897/1) to understand identification uncertainty and provide a strong scientific basis for implementing and planning ambient vibration tests. Part of the work was performed during the PhD of the first author at the University of Liverpool with a scholarship from the Chinese Scholarship Council, China. Currently, the first and third author are funded by Start-up Grant 130000-171207704/018 from Zhejiang University; and the second author by the grant SUG/4 (C120032000) at the Nanyang Technological University, Singapore. These financial supports are gratefully acknowledged. 2020-12-10T02:40:23Z 2020-12-10T02:40:23Z 2021 Journal Article Xie, Y.-L., Au, S.-K., & Li, B. (2021). Asymptotic identification uncertainty of well-separated modes in operational modal analysis with multiple setups. Mechanical Systems and Signal Processing, 152, 107382-. doi:10.1016/j.ymssp.2020.107382 0888-3270 https://hdl.handle.net/10356/145070 10.1016/j.ymssp.2020.107382 152 107382 en EP/N017897/1 130000-171207704/018 SUG/4 (C120032000) Mechanical Systems and Signal Processing © 2020 Elsevier. All rights reserved. This paper was published in Mechanical Systems and Signal Processing and is made available with permission of Elsevier. application/pdf |
| spellingShingle | Engineering::Civil engineering BAYOMA Cramer-Rao Bound Xie, Yan-Long Au, Siu-Kui Li, Binbin Asymptotic identification uncertainty of well-separated modes in operational modal analysis with multiple setups |
| title | Asymptotic identification uncertainty of well-separated modes in operational modal analysis with multiple setups |
| title_full | Asymptotic identification uncertainty of well-separated modes in operational modal analysis with multiple setups |
| title_fullStr | Asymptotic identification uncertainty of well-separated modes in operational modal analysis with multiple setups |
| title_full_unstemmed | Asymptotic identification uncertainty of well-separated modes in operational modal analysis with multiple setups |
| title_short | Asymptotic identification uncertainty of well-separated modes in operational modal analysis with multiple setups |
| title_sort | asymptotic identification uncertainty of well separated modes in operational modal analysis with multiple setups |
| topic | Engineering::Civil engineering BAYOMA Cramer-Rao Bound |
| url | https://hdl.handle.net/10356/145070 |
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