Bayesian operational modal analysis based on modalcomponent sampling

摘要：

　　A new Bayesian modal-component-sampling system identification(Bayes-ModeID)method is presented in this paper.This method can efficiently identify the modal parameters of civil engineering structures under different operational conditions even when the number of measured degrees of freedom(DOFs)is large.The mathematical model of the dynamic system is constructed with the modal parameters being the system parameters and the posterior probability density function(PDF)of the modal parameters is formulated using Bayes theorem.Bayesian modal analysis is conducted through sampling from the posterior PDF of the modal parameters.The modal-component-sampling algorithm is tailor made for the efficient sampling.Without assuming a particular form for the posterior PDF,the most probable values(MPVs)of the modal parameters can be obtained together with the corresponding posterior uncertainties based on the generated samples.Bayes-ModeID is illustrated in a case study of modal analysis of a shear building model.The computational efficiency is shown in the study.The identified modal parameters together with the uncertainties provide insights for operational analysis problems.

关键词： Modal component sampling Bayesian operational modal analysis field test

作者: H.F.Lam J.H.Yang J.L.Beck

作者单位: Department of Architecture and Civil Engineering,City University of Hong Kong,Hong Kong,China Research Institute of Structural Engineering and Disaster Reduction,College of Civil Engineering,Ton Division of Engineering and Applied Science,California Institute of Technology,Pasadena,CA,U.S.A.

会议类型: 国际会议

会议名称: The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)

会议地点: 青岛

会议语种:英文

页码: 1825-1832

在线出版日期: 2018-07-22（万方平台首次上网日期，不代表论文的发表时间）