Smart Structures and Systems

  • 제18권3호
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  • Pages.585-599
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  • 2016
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Force monitoring of steel cables using vision-based sensing technology: methodology and experimental verification

  • Ye, X.W. (Department of Civil Engineering, Zhejiang University) ;
  • Dong, C.Z. (Department of Civil Engineering, Zhejiang University) ;
  • Liu, T. (Department of Civil Engineering, Zhejiang University)
  • 투고 : 2015.08.07
  • 심사 : 2016.03.01
  • 발행 : 2016.09.25
⟨ 이전 논문 다음 논문 ⟩

초록

Steel cables serve as the key structural components in long-span bridges, and the force state of the steel cable is deemed to be one of the most important determinant factors representing the safety condition of bridge structures. The disadvantages of traditional cable force measurement methods have been envisaged and development of an effective alternative is still desired. In the last decade, the vision-based sensing technology has been rapidly developed and broadly applied in the field of structural health monitoring (SHM). With the aid of vision-based multi-point structural displacement measurement method, monitoring of the tensile force of the steel cable can be realized. In this paper, a novel cable force monitoring system integrated with a multi-point pattern matching algorithm is developed. The feasibility and accuracy of the developed vision-based force monitoring system has been validated by conducting the uniaxial tensile tests of steel bars, steel wire ropes, and parallel strand cables on a universal testing machine (UTM) as well as a series of moving loading experiments on a scale arch bridge model. The comparative study of the experimental outcomes indicates that the results obtained by the vision-based system are consistent with those measured by the traditional method for cable force measurement.

키워드

과제정보

연구 과제 주관 기관 : National Science Foundation of China

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  2. Stay cable tension estimation using a vision-based monitoring system under various weather conditions vol.7, pp.3, 2017, https://doi.org/10.1007/s13349-017-0226-7
  3. Identification of structural dynamic characteristics based on machine vision technology 2018, https://doi.org/10.1016/j.measurement.2017.09.043
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  5. Analysis on physical and mechanical performance and damage mechanism of steel strand under coupling effects of load and environment pp.09475117, 2018, https://doi.org/10.1002/maco.201810259
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