• 更多栏目

    侯吉林

    • 副教授     博士生导师   硕士生导师
    • 性别:男
    • 毕业院校:哈尔滨工业大学
    • 学位:博士
    • 所在单位:土木工程系
    • 学科:结构工程
    • 办公地点:建设工程学院4号楼433
    • 电子邮箱:houjilin@dlut.edu.cn

    访问量:

    开通时间:..

    最后更新时间:..

    Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses

    点击次数:

    论文类型:期刊论文

    第一作者:Zhang, Qingxia

    通讯作者:Hou, JL (reprint author), Dalian Univ Technol, Dept Civil Engn, Dalian 116023, Peoples R China.; Hou, JL (reprint author), Dalian Univ Technol, State Key Lab Coastal & Offshore Engn, Dalian 116023, Peoples R China.

    合写作者:Hou, Jilin,Jankowski, Lukasz

    发表时间:2020-01-01

    发表刊物:SENSORS

    收录刊物:EI、SCIE

    卷号:20

    期号:2

    关键字:structural health monitoring; damage identification; vehicle bump; additional virtual mass; bridge

    摘要:Structural damage identification plays an important role in providing effective evidence for the health monitoring of bridges in service. Due to the limitations of measurement points and lack of valid structural response data, the accurate identification of structural damage, especially for large-scale structures, remains difficult. Based on additional virtual mass, this paper presents a damage identification method for bridges using a vehicle bump as the excitation. First, general equations of virtual modifications, including virtual mass, stiffness, and damping, are derived. A theoretical method for damage identification, which is based on additional virtual mass, is formulated. The vehicle bump is analyzed, and the bump-induced excitation is estimated via a detailed analysis in four periods: separation, free-fall, contact, and coupled vibrations. The precise estimation of bump-induced excitation is then applied to a bridge. This allows the additional virtual mass method to be used, which requires knowledge of the excitations and acceleration responses in order to construct the frequency responses of a virtual structure with an additional virtual mass. Via this method, a virtual mass with substantially more weight than a typical vehicle is added to the bridge, which provides a sufficient amount of modal information for accurate damage identification while avoiding the bridge overloading problem. A numerical example of a two-span continuous beam is used to verify the proposed method, where the damage can be identified even with 15% Gaussian random noise pollution using a 1-degree of freedom (DOF) car model and 4-DOF model.