EMD-based random decrement technique for modal parameter identification of an existing railway bridge

Vibrational measurement data are often nonstationary and modal parameter identification based on these data is of practical value for structural health monitoring and condition assessment. The empirical mode decomposition (EMD) is a most recent tool for analysis of nonstationary signals. An EMD-base...

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Bibliographic Details
Published in:Engineering structures 2011-04, Vol.33 (4), p.1348-1356
Main Authors: He, X.H., Hua, X.G., Chen, Z.Q., Huang, F.L.
Format: Article
Language:English
Subjects:
Applied sciences
Bridges
Bridges (railroad)
Bridges (structures)
Buildings. Public works
Computation methods. Tables. Charts
Damping
Decomposition
Empirical mode decomposition (EMD)
Exact sciences and technology
Health monitoring
Mathematical models
Measurements. Technique of testing
Metal bridges
Monitoring
Nonstationary
Parameter identification
Polypropylenes
Random decrement (RD) technique
Steel bridges
Structural analysis. Stresses
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Summary:Vibrational measurement data are often nonstationary and modal parameter identification based on these data is of practical value for structural health monitoring and condition assessment. The empirical mode decomposition (EMD) is a most recent tool for analysis of nonstationary signals. An EMD-based random decrement (RD) technique is presented to identify modal parameters from monitoring vibrational data. The nonstationary measurement data are first decomposed into a series of quasi-stationary intrinsic mode functions (IMFs) by EMD. The RD technique is then applied to the selected IMFs to obtain the free-decay response. The modal frequencies and damping ratios are finally identified from the free-decay response by minimizing the error between the measured free-decay responses and the predicted responses from a parametric model. The present method is applied to extract the modal parameters of the Nanjing Yangtze River Bridge from the measured responses. The identification result is compared to those from finite element analysis as well as from the experimental result identified with the peak-picking (PP) method. In addition, the modal frequencies of the bridge loaded with heavy trains are also identified and compared to the ‘empty’ bridge. The EMD-based random decrement (RD) technique provides an effective and promising tool for modal parameter identification for large bridges and other structures.
ISSN:0141-0296
1873-7323
DOI:10.1016/j.engstruct.2011.01.012