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A strain-based wire breakage identification algorithm for unbonded PT tendons

  • Abdullah, A.B.M. (Department of Civil and Coastal Engineering, University of Florida) ;
  • Rice, Jennifer A. (Department of Civil and Coastal Engineering, University of Florida) ;
  • Hamilton, H.R. (Department of Civil and Coastal Engineering, University of Florida)
  • Received : 2014.08.13
  • Accepted : 2014.12.02
  • Published : 2015.09.25

Abstract

Tendon failures in bonded post-tensioned bridges over the last two decades have motivated ongoing investigations on various aspects of unbonded tendons and their monitoring methods. Recent research shows that change of strain distribution in anchor heads can be useful in detecting wire breakage in unbonded construction. Based on this strain variation, this paper develops a damage detection model that enables an automated tendon monitoring system to identify and locate wire breaks. The first part of this paper presents an experimental program conducted to study the strain variation in anchor heads by generating wire breaks using a mechanical device. The program comprised three sets of tests with fully populated 19-strand anchor head and evaluated the levels of strain variation with number of wire breaks in different strands. The sensitivity of strain variation with wire breaks in circumferential and radial directions of anchor head in addition to the axial direction (parallel to the strand) were investigated and the measured axial strains were found to be the most sensitive. The second part of the paper focuses on formulating the wire breakage detection framework. A finite element model of the anchorage assembly was created to demonstrate the algorithm as well as to investigate the asymmetric strain distribution observed in experimental results. In addition, as almost inevitably encountered during tendon stressing, the effects of differential wedge seating on the proposed model have been analyzed. A sensitivity analysis has been performed at the end to assess the robustness of the model with random measurement errors.

Keywords

References

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