TY - GEN
T1 - A comparison of correlation technique and random decrement algorithm for modal identification from nonstationary ambient vibration data only
AU - Lin, Chang Sheng
AU - Tseng, Tse Chuan
AU - Chen, June Rong
AU - Chiang, Dar Yun
PY - 2013
Y1 - 2013
N2 - Modal identification from response data only is studied for structural systems under nonstationary ambient vibration. By assuming the ambient excitation to be nonstationary white noise in the form of a product model and introducing a technique of curve fitting, the practical problem of insufficient data samples available for evaluating nonstationary correlation functions or randomdec signatures can be approximately resolved by first extracting the amplitude-modulating function from the response and then transforming the nonstationary responses into stationary ones. Modal-parameter identification can then be performed using the Ibrahim time-domain method in conjunction with the correlation technique and random decrement algorithm, respectively. A comparison of correlation technique and random decrement algorithm is demonstrated through numerical simulations, which also confirm the validity of the proposed method for identification of modal parameters from nonstationary ambient response data.
AB - Modal identification from response data only is studied for structural systems under nonstationary ambient vibration. By assuming the ambient excitation to be nonstationary white noise in the form of a product model and introducing a technique of curve fitting, the practical problem of insufficient data samples available for evaluating nonstationary correlation functions or randomdec signatures can be approximately resolved by first extracting the amplitude-modulating function from the response and then transforming the nonstationary responses into stationary ones. Modal-parameter identification can then be performed using the Ibrahim time-domain method in conjunction with the correlation technique and random decrement algorithm, respectively. A comparison of correlation technique and random decrement algorithm is demonstrated through numerical simulations, which also confirm the validity of the proposed method for identification of modal parameters from nonstationary ambient response data.
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U2 - 10.1007/978-1-4614-6747-2_87
DO - 10.1007/978-1-4614-6747-2_87
M3 - Conference contribution
AN - SCOPUS:84881044229
SN - 9781461467465
T3 - Lecture Notes in Electrical Engineering
SP - 755
EP - 764
BT - Intelligent Technologies and Engineering Systems
T2 - 2012 1st International Conference on Intelligent Technologies and Engineering Systems, ICITES 2012
Y2 - 13 December 2012 through 15 December 2012
ER -