Identification of modal strains in concrete beams at sub-microstrain amplitude excitation using fibre Bragg grating sensors mounted on a strain-amplifying transducer

Vibration-based damage identification is a non-destructive method that enables the health monitoring of civil infrastructures. It aims to detect the presence and location of damage by measuring changes in the vibration characteristics of these structures. Unfortunately, the most popular vibrational parameters – natural frequencies and modal displacements – have a low sensitivity to certain types of local damage. Modal strains and curvatures, on the other hand, can be sufficiently sensitive to local damage, but monitoring modal strains is challenging. Indeed, the strain amplitudes can be in the sub-microstrain range (<1 με) when considering ambient excitation which is too small for most conventional techniques. Here we show that such measurements can be successfully carried out in a quasi-distributed manner with fibre Bragg grating–based sensors that have been mounted on a dedicated strain-amplifying transducer. First, the authors report on lab-scale dynamic tests on a 5-m-long concrete beam, equipped with such transducers having a strain amplification of 62. The results show that the authors can identify the first three bending modes while the average strain level on the beam was only 0.06 με. Second, the authors present the first field test for these transducers conducted on a high-speed railway viaduct. The authors have succeeded to obtain six strain modes of the viaduct from the data collected with fibre Bragg gratings on the transducers at an average strain level of 0.067 με. To the best of the authors' knowledge, this is the first time that strain mode identification in operational conditions using strain-amplifying transducers was successful. This demonstration can be a starting point for the implementation of vibration-based damage identification in civil structures allowing the fulfillment of its long-standing promise.

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  • English

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  • Accession Number: 01775211
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jun 24 2021 4:43PM