Structural Monitoring and Maintenance

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Tension estimation method using natural frequencies for cable equipped with two dampers

  • Aiko Furukawa (Department of Urban Management, Graduate School of Engineering, Kyoto University) ;
  • Kenki Goda (Department of Urban Management, Graduate School of Engineering, Kyoto University) ;
  • Tomohiro Takeichi (Kobelco Wire Company, Ltd.)
  • Received : 2023.11.17
  • Accepted : 2023.12.20
  • Published : 2023.12.25
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Abstract

In cable structure maintenance, particularly for cable-stayed bridges, cable safety assessment relies on estimating cable tension. Conventionally, in Japan, cable tension is estimated from the natural frequencies of the cable using the higher-order vibration method. In recent years, dampers have been installed on cables to reduce cable vibrations. Because the higher-order vibration method is a method for damper-free cables, the damper must be removed to measure the natural frequencies of a cable without a damper. However, cables on some cable-stayed bridges have two dampers: one on the girder side and another on the tower side. Notably, removing and reinstalling the damper on the tower side are considerably more time- and labor-intensive. This paper introduces a tension estimation method for cables with two dampers, using natural frequencies. The proposed method was validated through numerical simulation and experiment. In the numerical tests, without measurement error in the natural frequencies, the maximum estimation error among 100 models was 3.3%. With measurement error of 2%, the average estimation error was within 5%, with a maximum error of 9%. The proposed method has high accuracy because the higher-order vibration method for a damper-free cable still has an estimation error of 5%. The experimental verification emphasizes the importance of accurate damper modeling, highlighting potential discrepancies between existing damper design formula and actual damper behavior. By revising the damper formula, the proposed method achieved accurate cable tension estimation, with a maximum estimation error of approximately 10%.

Keywords

Acknowledgement

We thank Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript.

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