Quantification of Statistical Error in the Estimate of Strain Power Spectral Density Transmissibility for Operational Strain Modal Analysis
Author(s): |
Qian Sun
Wang-Ji Yan Wei-Xin Ren Lin-Bo Cao Hai-Yi Wu |
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Medium: | journal article |
Language(s): | English |
Published in: | Structural Control and Health Monitoring, February 2023, v. 2023 |
Page(s): | 1-23 |
DOI: | 10.1155/2023/6661720 |
Abstract: |
The use of strain modes in structural health monitoring has been constantly increasing because of their superior sensitivity to local structural anomalies. This study aims to investigate the applicability and robustness of power spectral density transmissibility (PSDT) in operational strain modal analysis (OSMA). By noting that OSMA in the frequency domain is vulnerable to the error of spectral estimates, uncertainty quantification stemming from strain spectral estimates and the error propagation analysis in OSMA are conducted from an analytical perspective. The main contributions include the following: (i) the mean and variance of strain PSDT estimates are asymptotically derived based on statistical moment theory and the statistics of PSD estimate error, (ii) the coefficients of variation (c.o.v.) of the strain PSDT estimate and strain spectral estimates are compared with each other through asymptotic analysis to elaborate the robustness of strain PSDT, and (iii) the variability of the strain mode shape is quantified based on the asymptotic formula of strain PSDT estimates tending to local minima of asymptotic zero variance at the resonances. The accuracy and efficiency of the quantification and propagation analysis are validated through numerical and experimental test data accompanied by various parametric studies. |
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data sheet - Reference-ID
10734861 - Published on:
03/09/2023 - Last updated on:
03/09/2023