Journal of the Korea institute for structural maintenance and inspection (한국구조물진단유지관리공학회 논문집)

Korea Institute for Structural Maintenance Inspection (한국구조물진단유지관리공학회)
권호 표지
DOI QR코드

DOI QR Code

Vision-based Method for Estimating Cable Tension Using the Stay Cable Shape

사장재 케이블 형태를 이용하여 케이블 장력을 추정하는 영상기반 방법

  • 김진수 (국토안전관리원 특수교관리실 여수사무소) ;
  • 박재봉 (국토안전관리원 경영관리실) ;
  • 이덕근 (국토안전관리원 특수시설관리실) ;
  • 박동욱 (부산대학교 지진방재연구센터) ;
  • 김성완 (부산대학교 지진방재연구센터)
  • Received : 2024.01.12
  • Accepted : 2024.02.05
  • Published : 2024.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

Due to advancements in construction technology and analytical tools, an increasing number of cable-stayed bridges have been designed and constructed in recent years. A cable is a structural element that primarily transmits the main load of a cable-stayed bridge and plays the most crucial role in reflecting the overall condition of the entire bridge system. In this study, a vision-based method was applied to estimate the tension of the stay cables located at a long distance. To measure the response of a cable using a vision-based method, it is necessary to install feature points or targets on the cable. However, depending on the location of the point to be measured, there may be no feature points in the cable, and there may also be limitations in installing the target on the cable. Hence, it is necessary to find a way to measure cable response that overcomes the limitations of existing vision-based methods. This study proposes a method for measuring cable responses by utilizing the characteristics of cable shape. The proposed method involved extracting the cable shape from the acquired image and determining the center of the extracted cable shape to measure the cable response. The extracted natural frequencies of the vibration mode were obtained using the measured responses, and the tension was estimated by applying them to the vibration method. To verify the reliability of the vision-based method, cable images were obtained from the Hwatae Bridge in service under ambient vibration conditions. The reliability of the method proposed in this study was confirmed by applying it to the vibration method using a vision-based approach, resulting in estimated tensions with an error of less than 1% compared to tensions estimated using an accelerometer.

건설 기술과 해석 도구의 발전으로 인해 최근에는 점점 더 많은 사장교가 설계되고 건설되었다. 케이블은 사장교의 주요한 하중을 전달하는 부재이며 일반적으로 전체 교량 시스템의 상태를 반영하는 데 가장 중요한 역할을 한다. 이 연구에서는 원거리에 위치한 사장재 케이블의 장력을 추정하기 위하여 영상기반 방법을 적용하였다. 영상기반 방법을 이용하여 케이블의 응답을 측정하기 위해서는 케이블에 특이점 또는 타겟의 설치가 필요하다. 그러나 측정하고자 하는 지점의 위치에 따라 케이블에 특이점이 존재하지 않을 수 있으며 또한 케이블에 타겟의 설치가 어려울 수 있는 한계가 존재한다. 따라서 기존의 영상기반 방법의 한계를 극복하여 케이블 응답을 측정하는 방법이 필요하다. 이 연구에서는 케이블 형태의 특징을 이용하여 케이블 응답을 측정하는 방법을 제시하였다. 제시된 방법은 획득된 이미지에서 케이블 형태를 추출하였으며 추출된 케이블 형태의 중심을 산정하여 케이블 응답을 측정하였다. 측정된 응답을 이용하여 진동모드에 대한 고유진동수들을 추출하였으며 진동법에 적용하여 장력을 추정하였다. 영상기반 방법의 신뢰성을 확인하기 위해 공용 중인 화태대교에서 케이블 이미지를 상시진동 조건에서 획득하였다. 영상기반 방법을 이용하여 진동법에 적용하여 추정된 장력은 가속도 센서를 이용하여 추정된 장력과 1% 이내의 오차로 이 연구에서 제시된 방법의 신뢰성을 확인할 수 있었다.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2021R1A2C1012093).

References

  1. Zhang, L., Qiu, G., and Chen, Z. (2021), Structural health monitoring methods of cables in cable-stayed bridge: A review, Measurement, 168(2021), 108343.
  2. Nazarian, E., Ansari, F., Zhang, X., and Taylor, T. (2016), Detection of tension loss in cables of cable-stayed bridges by distributed monitoring of bridge deck strains, Journal of Structural Engineering, 142(6), 04016018.
  3. Kim, S. W., Park, D. U., Kim, J. S., Park, S. S., and Park, J. B. (2023a), Tension measurement of stay cables in consideration with image including vehicle, Journal of the Korea Institute for Structural Maintenance and Inspection, 27(2), 58-66 (in Korean).
  4. Cho, S. J., Yim, J. S., Shin, S. W., Jung, H. J., Yun, C. B., and Wang, M. L., (2013), Comparative field study of cable tension measurement for a cable-stayed bridge, Journal of Bridge Engineering, 18(8), 748-757.
  5. Kangas, S. Helmicki, A., Hunt, V., Sexton, R., and Swanson, J. (2012), Cable-stayed bridges: case study for ambient vibration-based cable tension estimation, Journal of Bridge Engineering, 17(6), 839-846. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000364
  6. Shimada, T. (1994), Estimating method of cable tension from natural frequency of high mode, Doboku Gakkai Rombun-Hokokushu/Proceedings of the Japan Society of Civil Engineers, 501, 163-171. https://doi.org/10.2208/jscej.1994.501_163
  7. Zui, H., Shinke, T., and Namita, Y. (1996), Practical formulas for estimation of cable tension by vibration method, Journal of Structural Engineering, 122(6), 651-656. https://doi.org/10.1061/(ASCE)0733-9445(1996)122:6(651)
  8. Li, H., Zhang, F., and Jin, Y. (2014), Real-time identification of time-varying tension in stay cables by monitoring cable transversal acceleration, Structural Control and Health Monitoring, 21(7), 1100-1117. https://doi.org/10.1002/stc.1634
  9. Feng, D., Scarangello, T., Feng, M. Q., and Ye, Q. (2017), Cable tension force estimate using novel noncontact vision-based sensor, Measurement, 99, 44-52. https://doi.org/10.1016/j.measurement.2016.12.020
  10. Chen, C. C., Wu, W. H., Tseng, H. Z., Chen, C. H., and Lai, G. (2015), Application of digital photogrammetry techniques in identifying the mode shape ratios of stay cables with multiple camcorders, Measurement, 75, 134-146. https://doi.org/10.1016/j.measurement.2015.07.037
  11. Kim, S. W., Park, D. U., Kim, J. S., and Park, J. B. (2023b), Estimating tension of a prestressed concrete cable-stayed bridge under construction and traffic use conditions using a vision-based system, Structures, 47, 299-312. https://doi.org/10.1016/j.istruc.2022.11.067
  12. Canny J. (1986), A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8, 679-698.
  13. Kim, Y. (2016), Development of Crack Recognition System for Concrete Structure Using Image Processing Method, Journal of Korean Institute of Information Technology, 14(10), 163-168 (in Korean). https://doi.org/10.14801/jkiit.2016.14.10.163
  14. Hild, F., and Roux, S. (2006), Digital image correlation: From displacement measurement to identification of elastic properties-a review, Strain, 42(2), 69-80. https://doi.org/10.1111/j.1475-1305.2006.00258.x