Computational Technology Resources - CCC

E. Rubino, M. Pavlic, "Fibre Optic Sensing: Modified Spectral Flatness Approach for Robust Train Localisation", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 23.9, 2022, doi:10.4203/ccc.1.23.9

Keywords: fibre optic sensing, distributed acoustic sensing, train localisation, spectral flatness, power spectral density, entropy spectral flatness.

Abstract

This paper presents a novel metric for the analysis of Distributed Acoustic Sensing (DAS) data for train localisation. Instead of using the average signal power to detect trains, the presented method uses a modified measure of the Spectral Flatness (SF), called Entropy Spectral Flatness (ESF), which overcomes the numerical instabilities of the traditional SF. This measure is independent of the signal dynamic range and requires no previous calibration. A comparison between the power and ESF approaches is shown and discussed. Ground truth data was also available and was used to compare the values of the position, speed, and length of trains measured using the ESF. The results show that our approach provides results that largely meet the railways localisation requirements.

download the full-text of this paper (PDF, 8756 Kb)

go to the previous paper
go to the next paper
return to the table of contents
return to the volume description

	Computational & Technology Resources an online resource for computational, engineering & technology publications
	not logged in - login
Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 1 PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 23.9 Fibre Optic Sensing: Modified Spectral Flatness Approach for Robust Train Localisation E. Rubino and M. Pavlic M2C ExpertControl GmbH, Offenberg, Germany doi:10.4203/ccc.1.23.9 Full Bibliographic Reference for this paper E. Rubino, M. Pavlic, "Fibre Optic Sensing: Modified Spectral Flatness Approach for Robust Train Localisation", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 23.9, 2022, doi:10.4203/ccc.1.23.9 Keywords: fibre optic sensing, distributed acoustic sensing, train localisation, spectral flatness, power spectral density, entropy spectral flatness. Abstract This paper presents a novel metric for the analysis of Distributed Acoustic Sensing (DAS) data for train localisation. Instead of using the average signal power to detect trains, the presented method uses a modified measure of the Spectral Flatness (SF), called Entropy Spectral Flatness (ESF), which overcomes the numerical instabilities of the traditional SF. This measure is independent of the signal dynamic range and requires no previous calibration. A comparison between the power and ESF approaches is shown and discussed. Ground truth data was also available and was used to compare the values of the position, speed, and length of trains measured using the ESF. The results show that our approach provides results that largely meet the railways localisation requirements. download the full-text of this paper (PDF, 8756 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
Back to top	©Civil-Comp Limited 2023 - terms & conditions