Optical fibre-based sensors for distributed strain monitoring of asphalt pavements

Abstract

Strain distribution of asphalt pavement varies in transverse and longitudinal directions, and distresses, such as cracks, ruts and settlements, often occur randomly, which can be efficiently measured by distributed optical fibre sensing technology. As bare optical fibre is weak to resist shear and torsion forces during pavement construction, the protective technique is required. Therefore, a flexible asphalt-mastic packaged optical fibre sensor was developed in this research for distributed strain monitoring of asphalt pavement. Theoretical analysis on strain transfer of the optical fibre-based sensors embedded in asphalt pavement was conducted to improve the design of the protective layer and remove the strain transfer error. Afterwards, laboratory tests on the asphalt concrete beam were carried out to validate the performance of the sensor. Finally, the proposed sensors were applied to detect the in situ performance of urban asphalt pavement under temperature and traffic loads. The results indicate that the proposed optical fibre sensor detects the distributed strain of asphalt pavement effectively, and the in situ data show significant effects of temperature and traffic loads on asphalt concrete course. This research contributes to the full-scale monitoring and health assessment of large-span pavement.

Keywords:

• Optical fibre sensor
• strain transfer analysis
• error modification
• distributed strain monitoring
• asphalt pavement

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Corrigendum

Acknowledgements

The writers are greatly appreciative of the editors and referees for spending time in attentively reading and checking this article. This work is supported by National Science and Technology Support Project (grant number 2011BAK02B01) and State 863 Project (grant number 2014AA110401). Special thanks are given to Prof. Zhi Zhou from Dalian University of Technology.

Additional information

Funding

This work is supported by National Science and Technology Support Project [grant number 2011BAK02B01] and State 863 Project [grant number 2014AA110401].