Details
| Original language | English |
|---|---|
| Number of pages | 16 |
| Volume | 50-51 |
| Publication status | Published - Jan 2015 |
Publication series
| Name | Mechanical Systems and Signal Processing |
|---|---|
| Publisher | Academic Press Inc. |
| ISSN (Print) | 0888-3270 |
Abstract
This paper deals with the identification of a stochastic computational model using experimental eigenfrequencies and mode shapes. In the presence of randomness, it is difficult to construct a one-to-one correspondence between the results provided by the stochastic computational model and the experimental data because of the random modes crossing and veering phenomena that may occur from one realization to another one. In this paper, this correspondence is constructed by introducing an adapted transformation for the computed modal quantities. Then the transformed computed modal quantities can be compared with the experimental data in order to identify the parameters of the stochastic computational model. The methodology is applied to a booster pump of thermal units for which experimental modal data have been measured on several sites.
Keywords
- Computational stochastic dynamics, Experimental modal analysis, Mode crossing, Model identification, Structural dynamics
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Computer Science(all)
- Signal Processing
- Engineering(all)
- Civil and Structural Engineering
- Engineering(all)
- Aerospace Engineering
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computer Science Applications
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2015. 16 p. (Mechanical Systems and Signal Processing).
Research output: Book/Report › Special issue › Research › peer review
}
TY - BOOK
T1 - Model identification in computational stochastic dynamics using experimental modal data
T2 - Probabilistic Engineering Mechanics, 38, 102–179
A2 - Beer, Michael
A2 - Kougioumtzoglou, Ioannis
A2 - Naess, Arvid
N1 - Funding information: This research work has been carried out in the context of the FUI 2012–2015 SICODYN Project (pour des SImulations crédibles via la COrrélation calculs-essais et l?estimation des incertitudes en DYNamique des structures). The support of the FUI (Fonds Unique Interministériel) (Grant No. F1202017 Z ) is gratefully acknowledged.
PY - 2015/1
Y1 - 2015/1
N2 - This paper deals with the identification of a stochastic computational model using experimental eigenfrequencies and mode shapes. In the presence of randomness, it is difficult to construct a one-to-one correspondence between the results provided by the stochastic computational model and the experimental data because of the random modes crossing and veering phenomena that may occur from one realization to another one. In this paper, this correspondence is constructed by introducing an adapted transformation for the computed modal quantities. Then the transformed computed modal quantities can be compared with the experimental data in order to identify the parameters of the stochastic computational model. The methodology is applied to a booster pump of thermal units for which experimental modal data have been measured on several sites.
AB - This paper deals with the identification of a stochastic computational model using experimental eigenfrequencies and mode shapes. In the presence of randomness, it is difficult to construct a one-to-one correspondence between the results provided by the stochastic computational model and the experimental data because of the random modes crossing and veering phenomena that may occur from one realization to another one. In this paper, this correspondence is constructed by introducing an adapted transformation for the computed modal quantities. Then the transformed computed modal quantities can be compared with the experimental data in order to identify the parameters of the stochastic computational model. The methodology is applied to a booster pump of thermal units for which experimental modal data have been measured on several sites.
KW - Computational stochastic dynamics
KW - Experimental modal analysis
KW - Mode crossing
KW - Model identification
KW - Structural dynamics
UR - http://www.scopus.com/inward/record.url?scp=84905828296&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2014.05.010
DO - 10.1016/j.ymssp.2014.05.010
M3 - Special issue
VL - 50-51
T3 - Mechanical Systems and Signal Processing
BT - Model identification in computational stochastic dynamics using experimental modal data
ER -