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    欧进萍

    • 教授     博士生导师   硕士生导师
    • 性别:男
    • 毕业院校:哈尔滨建筑大学
    • 学位:博士
    • 所在单位:建设工程学院
    • 电子邮箱:ojinping@dlut.edu.cn

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    An algorithm for damage localization in steel truss structures: Numerical simulation and experimental validation

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    论文类型:期刊论文

    发表时间:2013-09-01

    发表刊物:JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES

    收录刊物:SCIE、EI、Scopus

    卷号:24

    期号:14

    页面范围:1683-1698

    ISSN号:1045-389X

    关键字:Damage localization; fractal dimension; curvature method; steel truss structures; damage detection; damage identification; structural health monitoring

    摘要:It is imperative to study the damage detection methods of steel truss structures that are always employed in extreme environment. Accurate structural damage localization is still a challenge due to high noise and low accuracy of the structural finite element model. To develop a dependable damage localization technique for truss structural health monitoring, a novel idea of damage localization is proposed: the curvature difference method of strain waveform fractal dimension, based on fractal theory and curvature method. To validate the approach, a simply supported bailey steel truss benchmark model has been designed and constructed in the laboratory. Based on the model, both experimental and numerical simulation results using the procedure under pulse excitation indicate that it is feasible and effective to detect the change of boundary conditions and the stiffness reduction of a truss member. In addition, the proposed technique exhibits high-noise insusceptibility (e.g. it works for noise levels up to 20% for a 10% truss member stiffness reduction). Moreover, the proposed technology is robust against the accuracy of the finite element model of measured structures, which decrease the workload of model updating dramatically. All these lay a good foundation for its engineering application.