Identification of external load information using distributed optical fiber sensors embedded in an existing road pavement

Abstract

This paper describes field applications of distributed optical fiber sensors (DOFS) for monitoring the traffic load on an existing road. To investigate the optimal embedment depth for DOFS for pavement monitoring, a series of field tests was conducted by considering three embedment depths (10, 30, and 40 mm) and three moving loads (pedestrian, car and truck). The main objectives were to examine the performance of DOFS embedded in the pavement and investigate its suitability and sensitivity for obtaining information about moving loads at various depths from the road surface. Among the existing backscattering light technology, Rayleigh scattering-based Optical Frequency Domain Reflectometry (OFDR) was chosen in order to achieve a measurement of high-speed, high range, and good repeatability with a very high spatial resolution of 2.56 mm, all of which are necessary for monitoring dynamic responses due to moving loads. In addition, a data-processing method was developed based on a combination of a Hampel identifier and a low-pass filter, which proved to be effective in removing outliers and high-frequency noise from the raw measurement data, respectively. The results showed that it is not only possible to detect a moving load on a road, but that a wide range of information can also be obtained from the strains measured by DOFS, including the type of load, its speed, its weight, the number of axles, the axle spacings (in the case of a vehicle) and the traffic flow. With low maintenance costs, DOFS based on Rayleigh scattering OFDR could be used for collection of accurate and reliable traffic data when embedded in a pavement.