Low cost bridge load test: calculating bridge displacement from acceleration for load assessment calculations

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      Bridge failure to pass load capacity assessment is unfortunately not an uncommon problem in bridge engineering and it is a potentially expensive problem for the bridge owner. Using load test data to justify increase in assessed load capacity is recognised as a viable approach in professional codes of practice. However, load tests are rarely carried out in practice because traditionally they are expensive to conduct and may not always justify an increase in assessed load capacity. Therefore this paper proposes a simple, quick and reliable approach for bridge load testing. In particular a procedure to calculate the bridge displacement to a moving truck by double integration of bridge acceleration is presented. Integrating acceleration to calculate displacement is not a new approach, with authors reporting difficulties due to errors in acceleration signals and unknown initial conditions. Many of the previous approaches have focused on developing signal processing algorithms to correct for the signal errors and while some good results have been reported, typically the derived displacements are very sensitive to parameters used in the correction algorithm, such as passband filter frequencies. Consequently, without comparison with directly measured displacement data, reliability of the procedure cannot be established and errors quantified. Therefore in this study a stripped down procedure is applied placing emphasis instead on minimising the errors in the recorded acceleration by using appropriate hardware and developing a quality control procedure that allows the user to assess the likely accuracy of the calculated displacement signal. The effectiveness of the proposed approach is trialled in the laboratory and in the field, with an accuracy of ±0.5mm observed.
      Original languageEnglish
      Number of pages14
      Pages (from-to)358-374
      JournalEngineering Structures
      Journal publication date15 Jul 2017
      Volume143
      Early online date25 Apr 2017
      StatePublished - 15 Jul 2017

      ID: 125901345