A Computer Vision-based Method For Cable Tension Identification Of Bridge Structures

Cable-bearing bridges play an important role in the transport industry.As the main load-bearing element of cable-bearing bridges,the cables are susceptible to damage caused by traffic loads and the external environment,resulting in a reduction in their load-bearing capacity.As a result,cable failures can cause accidents and have a serious impact on social and economic development,so it is important to monitor the health of the cable forces of cable-bearing bridges.The traditional method of cable tension identification is a contact method,which requires the manual arrangement of cable tension identification sensors and has problems such as high cost and low efficiency.In this paper,the research on computer vision-based cable tension identification method can provide key technical support for the intelligent management and maintenance of cable-bearing bridges.The main work of this thesis is as follows:(1)A comprehensive introduction to the basic principles of the frequency method of cable tension identification,a systematic description of the basic principles of the motion amplification algorithm and the edge detection algorithm,and a comparative analysis of the characteristics and applicable scenarios of different motion amplification algorithms and edge detection algorithms.On the basis of this,by combining algorithms for motion amplification,edge detection and target tracking,a computer vision-based method for cable tension identification is proposed.(2)The experimental validation study of the computer vision-based cable tension identification method is carried out.The experimental device for cable tension identification was designed and fabricated,and the acceleration sensor-based cable tension identification method,the Eulerian motion amplification algorithm-based cable tension identification method and the Lucas-Kanade sparse optical flow method-based cable tension identification method were used to conduct comparative cable tension identification experiments to verify the feasibility of the Eulerian motion amplification algorithm-based cable tension identification method proposed in this paper.(3)A comprehensive research on the engineering application of the computer vision-based cable tension identification method was carried out.Using the arch bridge suspender of the Xinguang Bridge in Guangzhou as the cable tension identification object,the acceleration sensor-based cable tension identification method,the Eulerian motion amplification algorithm-based cable tension identification method and the Lucas-Kanade sparse optical flow method were used to carry out the real bridge cable tension identification respectively,verifying the engineering practicality of the Eulerian motion amplification algorithm-based cable tension identification method proposed in this paper.The research results show that compared with the traditional cable tension identification method,the proposed Eulerian motion amplification algorithm-based cable tension identification method has the advantages of simple operation,low cost,high efficiency and accuracy,which can effectively improve the automation and information level of cable tension identification.The research work in this paper also effectively expands the scope of application of computer vision in the field of structural vibration testing and further promotes the development of computer vision technology.