TY - GEN
T1 - Empirical Slow-Flow Identification for Structural Health Monitoring and Damage Detection
AU - Lee, Young S.
AU - McFarland, Michael
AU - Bergman, Lawrence A.
AU - Vakakis, Alexander F.
N1 - Funding Information:
This work was supported in part by the National Science Foundation of the United States through Grants CMMI-0927995 and CMMI-0928062.
PY - 2014
Y1 - 2014
N2 - We utilize the nonlinear system identification (NSI) methodology, which was recently developed based on the correspondence between analytical and empirical slow-flow dynamics. Performing empirical mode decomposition on the simulated or measured time series to extract intrinsic mode oscillations, we establish nonlinear interaction models, which invoke slowly-varying forcing amplitudes that can be computed from empirical slow-flows. By comparing the spatio-temporal variations of the nonlinear modal interactions for structures with defects and those for the underlying healthy structure, we will demonstrate that the proposed NSI method can not only explore the smooth/nonsmooth nonlinear dynamics caused by structural damage, but also the extracted vibration characteristics can directly be implemented for structural health monitoring and detecting damage locations. Starting with traditional tools such as the modal assurance criterion (MAC) and the coordinate MAC are utilized.
AB - We utilize the nonlinear system identification (NSI) methodology, which was recently developed based on the correspondence between analytical and empirical slow-flow dynamics. Performing empirical mode decomposition on the simulated or measured time series to extract intrinsic mode oscillations, we establish nonlinear interaction models, which invoke slowly-varying forcing amplitudes that can be computed from empirical slow-flows. By comparing the spatio-temporal variations of the nonlinear modal interactions for structures with defects and those for the underlying healthy structure, we will demonstrate that the proposed NSI method can not only explore the smooth/nonsmooth nonlinear dynamics caused by structural damage, but also the extracted vibration characteristics can directly be implemented for structural health monitoring and detecting damage locations. Starting with traditional tools such as the modal assurance criterion (MAC) and the coordinate MAC are utilized.
KW - Empirical mode decomposition
KW - Intrinsic modal oscillator
KW - Nonlinear interaction model
KW - Nonlinear system identification
KW - Structural health monitoring
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U2 - 10.1007/978-1-4614-6585-0_59
DO - 10.1007/978-1-4614-6585-0_59
M3 - Conference contribution
AN - SCOPUS:84883020471
SN - 9781461465843
T3 - Conference Proceedings of the Society for Experimental Mechanics Series
SP - 617
EP - 624
BT - Topics in Dynamics of Civil Structures- Proceedings of the 31st IMAC, A Conference on Structural Dynamics, 2013
T2 - 31st International Modal Analysis Conference on Structural Dynamics, IMAC 2013
Y2 - 11 February 2013 through 14 February 2013
ER -