Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses

Sensors

Łukasz Jankowski¹  Jilin Hou²  Qingxia Zhang³ 

[1] State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116023, China;;Department of Civil Engineering &School of Civil Engineering, Dalian Minzu University, Dalian 116600, China;

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

DOI  :  10.3390/s20020394

来源: DOAJ

【 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.

【 授权许可】

Unknown