Improved polyreference time domain method for modal identification using local or global noise removal techniques  

作　　者：HU Sau-Lon James BAO XingXian LI HuaJun 

机构地区：[1]Department of Ocean Engineering, University of Rhode Island, Narragansett, R102882-1197, USA [2]Department of Marine Engineering and Fluid Mechanics, China University of Petroleum (East China), Qingdao 266555, China [3]Shandong Provincial Key Lab of Ocean Engineering, Ocean University of China, Qingdao 266100, China

出　　处：《Science China(Physics,Mechanics & Astronomy)》2012年第8期1464-1474,共11页中国科学：物理学、力学、天文学（英文版）

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);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)

摘　　要：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.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.

关 键 词：modal identification model order determination noise removal structured low rank approximation 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN713[自动化与计算机技术—计算机科学与技术]