实验技术与管理2025，Vol.42Issue(7)：17-25,9.DOI:10.16791/j.cnki.sjg.2025.07.003
基于随机子空间法的振动台试验模态参数识别
Modal parameter identification in shaking table tests using stochastic subspace method:Taking the scale model of a super high-rise building as an example
摘要
Abstract
[Objective]Owing to their extreme height,extended fundamental frequencies,and complex mode shapes,supertall buildings have consistently posed challenges in seismic performance assessments,especially in regions experiencing high seismicity.As a widely adopted experimental approach,shaking table tests provide critical insights into the dynamic response and failure mechanisms of such structures under earthquake loading.A key step in such tests involves the identification of structural modal parameters,which traditionally relies on white noise excitation due to its broadband,uniformly distributed frequency content,and technical maturity.However,for the scaled models of supertall structures,which are typically characterized by reduced stiffness and low natural frequencies,long-duration white noise excitation can induce cumulative microdamage.Such subtle yet potentially irreversible changes,such as local cracking or stiffness degradation,may adversely influence the structural response under subsequent seismic excitations,thereby compromising the accuracy of performance evaluation.[Methods]This study investigates the feasibility of using a stochastic subspace identification(SSI-Dat)method for extracting the modal parameters of a scaled supertall building model directly from seismic response data,thereby avoiding potential model degradation associated with traditional white noise excitation.A series of shaking table tests are conducted under three levels of the seismic input(e.g.,minor,moderate,and major earthquakes),corresponding to a seismic fortification intensity of 7.The method utilizes measured acceleration time histories to construct a system observation matrix from which natural frequencies,damping ratios,and dominant mode shapes are extracted via subspace decomposition.To evaluate the reliability and accuracy of the SSI-Dat method,the identified modal parameters are compared with those obtained from white noise excitation using the frequency response function(FRF)method under identical test conditions.[Results]To validate the accuracy and reliability of the SSI-Dat method,the identified modal parameters are compared with those obtained through conventional white noise excitation using the FRF method after each seismic event.Results show that,under minor seismic excitation,the SSI-Dat method yields modal parameters that noticeably deviate from those derived via the white noise approach,likely due to insufficient energy input and limited excitation in high modes.Meanwhile,under moderate and major earthquake inputs,the identified modal parameters,especially fundamental frequencies and dominant mode shapes,exhibit good agreement with the white-noise-based results.This indicates that,as input energy increases,the dynamic response of the structure becomes richer in the modal content,thereby enhancing the effectiveness of subspace-based identification techniques.Throughout the tests,the structure mainly exhibits horizontal motion with minimal torsion.Post-test modal shifts indicate damage accumulation,especially under strong quakes.Despite local stiffness degradation and cracking,the model remains globally intact,retaining load-bearing capacity.This reflects the realistic seismic performance of the supertall building and validates the scaled model's structural fidelity.[Conclusions]This study demonstrates the feasibility and reliability of using the SSI-Dat method to identify the modal parameters of scaled supertall building models under seismic excitation.Compared to the conventional white-noise-based approach,this method avoids risks associated with prolonged artificial excitation and offers a more realistic representation of the structural dynamic characteristics.These findings provide a valuable methodological reference for future shaking table tests involving high-rise structures and contribute to the advancement of nonintrusive modal identification techniques in seismic tests.关键词
模态参数识别/随机子空间法/超高层缩尺模型/相似关系/振动台试验Key words
modal parameter identification/stochastic subspace method/scaled super high-rise model/similarity relation/shaking table tests分类
建筑与水利引用本文复制引用
张国伟,李建赢,张宏,秦昌安,杨昕雨..基于随机子空间法的振动台试验模态参数识别[J].实验技术与管理,2025,42(7):17-25,9.基金项目
首都科技条件平台2023年度北京建筑大学绩效考核后补助实施项目阶段性成果(Z24006) （Z24006）
