There is today ample evidence that fiber Bragg gratings (FBGs) distributed along a railway track can provide robust axle counting and bring numerous assets compared to competing technologies in this practical environment. This work brings two relevant originalities with respect to the state-of-the-art solutions. First, a study of the strain distribution in the rail cross-section is performed to determine the sensitivity according to the charge and the position on the rail. Secondly, the technology is deployed along the rail track as a smart object where the sensor head is composed of four FBG wavelength-division-multiplexed in a single telecommunication-grade optical fiber and interrogated by a miniaturized read-out device. Two FBGs ensure the detection of the train direction and another two bring the required redundancy to reach a safety integrity level (SIL) 4. The read-out unit has been specifically developed for the application and contains a vertical-cavity surface-emitting laser (VCSEL) and a photodiode driven by a high-speed microprocessor unit that processes the data and communicates the useful information, i.e., the number of axles. On-field tests confirm that the proposed approach makes the installation process easier while it democratizes the technology.
This paper reports on the development of a smart elastic textile band containing pre-strained fiber Bragg gratings (FBG) that was specifically designed with the ambition to dynamically measure the position of the backbone. To this aim, the textile band is 700 mm long and 60 mm wide. A piece of standard single-mode optical fiber, in which four fiber Bragg gratings were inscribed, is sewn on the band. Each FBG is glued on a 3D-printed pad in a pre-strained way, allowing the detection of FBG compression in addition to elongation. Measurements were performed on this sensing elastic band and the resulting sensitivity is a Bragg wavelength shift of 12 pm per mm of textile elongation. Validation tests were also carried out to highlight the sensitivity to compression and to show that the sensing system is capable of repeatability in a dynamic environment.
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