Experimental modeling of a middle-rise office building via ambient modal identification is presented. A 200-DOF (Dimension of freedom) test model is designed to correlate with finite element mode. A newly developed fr...Experimental modeling of a middle-rise office building via ambient modal identification is presented. A 200-DOF (Dimension of freedom) test model is designed to correlate with finite element mode. A newly developed frequency-spatial domain decomposition ( FSDD ) technique is used to identify modal characteristics of the full-size building by using ambient response measurements. In the interested frequency ranges of 0～4.5 Hz and 0～ 6.5 Hz altogether 9 bending and torsion modes are identified. As one of the major focuses of the project, the accurate damping estimation is conducted based on FSDD. The identified modal frequencies and mode shapes are utilized for finite element model tuning. Excellent agreement has been achieved with respect to the final tuned finite element (FE) model up to 9 modes.展开更多
Modal identification involves estimating the modal parameters, such as modal frequencies, damping ratios, and mode shapes, of a structural system from measured data. Under the condition that noisy impulse response sig...Modal identification involves estimating the modal parameters, such as modal frequencies, damping ratios, and mode shapes, of a structural system from measured data. Under the condition that noisy impulse response signals associated with multiple input and output locations have been measured, the primary objective of this study is to apply the local or global noise removal technique for improving the modal identification based on the polyreference time domain (PTD) method. While the traditional PTD method improves modal parameter estimation by over-specifying the computational model order to absorb noise, this paper proposes an approach using the actual system order as the computational model order and rejecting much noise prior to performing modal parameter estimation algorithms. Two noise removal approaches are investigated: a "local" approach which removes noise from one signal at a time, and a "global" approach which removes the noise of multiple measured signals simultaneously. The numerical investigation in this article is based on experimental measurements from two test setups: a cantilever beam with 3 inputs and 10 outputs, and a hanged plate with 4 inputs and 32 outputs. This paper demonstrates that the proposed noise-rejection method outperforms the traditional noise-absorption PTD method in several crucial aspects.展开更多
文摘Experimental modeling of a middle-rise office building via ambient modal identification is presented. A 200-DOF (Dimension of freedom) test model is designed to correlate with finite element mode. A newly developed frequency-spatial domain decomposition ( FSDD ) technique is used to identify modal characteristics of the full-size building by using ambient response measurements. In the interested frequency ranges of 0～4.5 Hz and 0～ 6.5 Hz altogether 9 bending and torsion modes are identified. As one of the major focuses of the project, the accurate damping estimation is conducted based on FSDD. The identified modal frequencies and mode shapes are utilized for finite element model tuning. Excellent agreement has been achieved with respect to the final tuned finite element (FE) model up to 9 modes.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51079134 and 51009124)the NSFC Major International Joint Research Project (Grant No. 51010009)+2 种基金the Program for Changjiang Scholars and Innovative Research Team in University (Grant No. PCSIRT 1086)the Natural Science Foundation of Shandong Province(Grant Nos. ZR2011EEQ022 and 2009ZRA05100)the Fundamental Research Funds for the Central Universities (Grant Nos. 27R1202008A and27R1002076A)
文摘Modal identification involves estimating the modal parameters, such as modal frequencies, damping ratios, and mode shapes, of a structural system from measured data. Under the condition that noisy impulse response signals associated with multiple input and output locations have been measured, the primary objective of this study is to apply the local or global noise removal technique for improving the modal identification based on the polyreference time domain (PTD) method. While the traditional PTD method improves modal parameter estimation by over-specifying the computational model order to absorb noise, this paper proposes an approach using the actual system order as the computational model order and rejecting much noise prior to performing modal parameter estimation algorithms. Two noise removal approaches are investigated: a "local" approach which removes noise from one signal at a time, and a "global" approach which removes the noise of multiple measured signals simultaneously. The numerical investigation in this article is based on experimental measurements from two test setups: a cantilever beam with 3 inputs and 10 outputs, and a hanged plate with 4 inputs and 32 outputs. This paper demonstrates that the proposed noise-rejection method outperforms the traditional noise-absorption PTD method in several crucial aspects.
