湖南大学学报（自然科学版）2024，Vol.51Issue(7)：72-82,11.DOI:10.16339/j.cnki.hdxbzkb.2024069
基于响应谱传递比估计误差的结构模态参数识别精度分析
Analytical of Structural Modal Parameter Identification Accuracy Based on Estimation Errors in Power Spectrum Density Transmissibility
摘要
Abstract
To investigate the statistical errors inherent in this classical process and its influence on PSDT measurements,based on the perturbation technique,the mean and variance of the quotient of the random variables are approximately expressed with the application of the statistical moment method.Then,the statistical moments of two response spectral estimates are substituted to derive the formulae for the mean and variance of the PSDT's amplitude regarding the coherence function of the response and the number of averaging segments in spectrum analysis.Based on this,the error law in the amplitude of the PSDT estimate at the resonance frequency is revealed to quantify the estimation error of the mode shape.It is found that the error in the PSDT's amplitude estimate at the resonances tends to a local minimum value,and the coefficient of variation is smaller than the counterparts of two associated response power spectrum densities.Finally,the accuracy of the derived error formulation in the paper is verified by vibration data from one numerical frame.Moreover,a parameter study regarding the influence of the selection of reference response,the time duration of measurements,and the type of window function on the PSDT and mode shape estimates is performed.The results show that using two basic responses of PSDT as the reference responses is beneficial to reduce the error in PSDT estimates and outcomes of modal analysis,and the standard variance of the estimate also decreases with the increasing time duration of measurements and finally to a specific limit.关键词
频谱误差/响应功率谱传递比/模态识别/误差分析/摄动法Key words
spectral error/power spectrum density transmissibility/modal analysis/error analysis/perturba-tion technique分类
交通工程引用本文复制引用
孙倩,颜王吉,任伟新..基于响应谱传递比估计误差的结构模态参数识别精度分析[J].湖南大学学报（自然科学版）,2024,51(7):72-82,11.基金项目
安徽省高校自然科学研究重点项目(2023AH052185),Key Projects of Natural Science Research in Colleges and Universities in Anhui Province(2023AH052185) （2023AH052185）
合肥学院人才科研基金项目(20RC30),Hefei University Talent ResearchFund Project(20RC30) （20RC30）
澳门科学技术发展基金(FDCT/017/2020/A1),the Science and Technology Development Fund,Macau SAR(FDCT/017/2020/A1) （FDCT/017/2020/A1）
深圳市科技创新委员会项目(KQTD20180412181337494,JSGG20210802093207022,ZDSYS20201020162400001),the Shenzhen Science and Technology Program(KQTD20180412181337494,JSGG20210802093207022,ZDSYS20201020162400001) （KQTD20180412181337494,JSGG20210802093207022,ZDSYS20201020162400001）
