A Computationally Efficient Algorithm for Real-Time Tracking the Abrupt Stiffness Degradations of Structural Elements

被引:35
|
作者
Lei, Ying [1 ,2 ]
Zhou, Huan [1 ]
Lai, Zhi-Lu [3 ]
机构
[1] Xiamen Univ, Dept Civil Engn, Xiamen, Peoples R China
[2] Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai 200092, Peoples R China
[3] Rice Univ, Dept Civil & Environm Engn, Houston, TX USA
基金
中国国家自然科学基金;
关键词
WAVELET NEURAL-NETWORK; DAMAGE DETECTION; ONLINE IDENTIFICATION; VARYING SYSTEMS; KALMAN FILTER; PHASE-I; MODEL; PARAMETER; 2-STAGE; BRIDGE;
D O I
10.1111/mice.12217
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Real-time structural identification and damage detection are necessary for on-line structural damage detection and optimal structural vibration control during severe loadings. Frequently, structural damage can be reflected in the stiffness degradation of structural elements. In this article, a time-domain three-stage algorithm with computational efficiency is proposed for real-time tracking the onsets, locations, and extents of abrupt stiffness degradations of structural elements using measurements of structural acceleration responses. Structural dynamic parameters before damage are recursively estimated in stage I. Then, the time instants and possible locations of degraded structural elements are detected by tracking the errors between the measured data and the corresponding estimated values in stage II. Finally, the exact locations and extents of stiffness degradations of structural elements are determined by solving simple constrained optimization problems in stage III. Both numerical examples and an experimental test are used to validate the proposed algorithm for real-time tracking the abrupt stiffness degradations of structural elements in linear or nonlinear structures using measurements of structural acceleration responses polluted by noises.
引用
收藏
页码:465 / 480
页数:16
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