Abstract

This paper presents a novelty approach to usage of the fiber-optic phase-based sensor in railway transportation. We designed and tested the real deployment of this sensor working on the principle of light interferences within optical fibers. The proposed construction of the sensor allowed to increase the sensitivity and thanks to this can be detected and calculated individual axles and wheels of tram vehicles. We performed long-time period measurements (April to September 2019) in diverse climatic conditions, including measurements of 642 tram passages (several different construction types) in real urban traffic. The detection accuracy level was slightly above 99.4 %.

Highlights

  • In order to maintain the safety of railway operation, it’s necessary to know the exact position and number of carriages within a rail vehicle

  • This paper directly follows and extends our previously published study [2] in which we present interferometric sensor primarily used for tram vehicle detection, as well as for detection of frequencies generated during trams passage

  • Our paper proposes innovative interferometric sensor based on Mach-Zehnder two-armed interferometer, when by the specific construction of measuring and reference arms, storing both couplers, and innovative design changes of the sensor measuring part led to increased sensibility in such a level that individual axles of tram vehicles could be detected with high accuracy of more than 99 %

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Summary

Introduction

In order to maintain the safety of railway operation (tram or train), it’s necessary to know the exact position and number of carriages within a rail vehicle. Wheel detectors or axle counters are used for this purpose. They are characterized by relatively old technology methods with gradual descending reliability. This paper directly follows and extends our previously published study [2] in which we present interferometric sensor primarily used for tram vehicle detection, as well as for detection of frequencies generated during trams passage. We point out the ability to detect individual tram axles.

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