Element Classification and Statistical Damage Detection Method for Spatial Frame Structures
Based on the strain mode shapes (SMS), a statistical damage detection approach is proposed and applied to the spatial frame structures. The element stiffness reduction parameters estimated from different modal data sets taken as an index for damages at the corresponding structural locations. And then a Bayesian statistical method employing SMS and the first rank perturbation matrix theory is utilized to obtain the posterior probability density function (PDF) of the parameters. The most probable values and standard deviations of the parameters are determined through maximizing the PDF. To reduce the number of the parameters, a substructure approach is followed in which elements are divided into several groups based on similarity degrees. By this means, damages are detected in two steps: all the possible damaged elements are identified at first, and then damage locations and sizes are detected. The performance of the proposed approach is demonstrated by simulating analysis.
Damage detection Strain mode shape Bayesian statistical method Matrix perturbation theory
Gongbiao Li Bo Chen Weilian Qu
Hubei Key Laboratory of Roadway Bridge & Structural Engineering, Wuhan University of Technology, Wuhan, China
国际会议
南京
英文
429-435
2007-10-16（万方平台首次上网日期，不代表论文的发表时间）