Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | Intelligent Technologies and Engineering Systems |
| Pages | 755-764 |
| Number of pages | 10 |
| DOIs | |
| Publication status | Published - 2013 Aug 8 |
| Event | 2012 1st International Conference on Intelligent Technologies and Engineering Systems, ICITES 2012 - Changhua, Taiwan Duration: 2012 Dec 13 → 2012 Dec 15 |
Publication series
| Name | Lecture Notes in Electrical Engineering |
|---|---|
| Volume | 234 LNEE |
| ISSN (Print) | 1876-1100 |
| ISSN (Electronic) | 1876-1119 |
Other
| Other | 2012 1st International Conference on Intelligent Technologies and Engineering Systems, ICITES 2012 |
|---|---|
| Country | Taiwan |
| City | Changhua |
| Period | 12-12-13 → 12-12-15 |
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All Science Journal Classification (ASJC) codes
- Industrial and Manufacturing Engineering
Cite this
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A comparison of correlation technique and random decrement algorithm for modal identification from nonstationary ambient vibration data only. / Lin, Chang Sheng; Tseng, Tse Chuan; Chen, June Rong; Chiang, Dar Yun.
Intelligent Technologies and Engineering Systems. 2013. p. 755-764 (Lecture Notes in Electrical Engineering; Vol. 234 LNEE).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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 - 2013/8/8
Y1 - 2013/8/8
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.
UR - http://www.scopus.com/inward/record.url?scp=84881044229&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881044229&partnerID=8YFLogxK
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
ER -