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Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh
We present DR-Train, the first long-term open-access dataset recording dynamic responses from in-service light rail vehicles. Specifically, the dataset contains measurements from multiple sensor channels mounted on two in-service light rail vehicles that run on a 42.2-km light rail network in the ci...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6690915/ https://www.ncbi.nlm.nih.gov/pubmed/31406119 http://dx.doi.org/10.1038/s41597-019-0148-9 |
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author | Liu, Jingxiao Chen, Siheng Lederman, George Kramer, David B. Noh, Hae Young Bielak, Jacobo Garrett, James H. Kovačević, Jelena Bergés, Mario |
author_facet | Liu, Jingxiao Chen, Siheng Lederman, George Kramer, David B. Noh, Hae Young Bielak, Jacobo Garrett, James H. Kovačević, Jelena Bergés, Mario |
author_sort | Liu, Jingxiao |
collection | PubMed |
description | We present DR-Train, the first long-term open-access dataset recording dynamic responses from in-service light rail vehicles. Specifically, the dataset contains measurements from multiple sensor channels mounted on two in-service light rail vehicles that run on a 42.2-km light rail network in the city of Pittsburgh, Pennsylvania. This dataset provides dynamic responses of in-service trains via vibration data collected by accelerometers, which enables a low-cost way of monitoring rail tracks more frequently. Such an approach will result in more reliable and economical ways to monitor rail infrastructure. The dataset also includes corresponding GPS positions of the trains, environmental conditions (including temperature, wind, weather, and precipitation), and track maintenance logs. The data, which is stored in a MAT-file format, can be conveniently loaded for various potential uses, such as validating anomaly detection and data fusion as well as investigating environmental influences on train responses. |
format | Online Article Text |
id | pubmed-6690915 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66909152019-08-19 Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh Liu, Jingxiao Chen, Siheng Lederman, George Kramer, David B. Noh, Hae Young Bielak, Jacobo Garrett, James H. Kovačević, Jelena Bergés, Mario Sci Data Data Descriptor We present DR-Train, the first long-term open-access dataset recording dynamic responses from in-service light rail vehicles. Specifically, the dataset contains measurements from multiple sensor channels mounted on two in-service light rail vehicles that run on a 42.2-km light rail network in the city of Pittsburgh, Pennsylvania. This dataset provides dynamic responses of in-service trains via vibration data collected by accelerometers, which enables a low-cost way of monitoring rail tracks more frequently. Such an approach will result in more reliable and economical ways to monitor rail infrastructure. The dataset also includes corresponding GPS positions of the trains, environmental conditions (including temperature, wind, weather, and precipitation), and track maintenance logs. The data, which is stored in a MAT-file format, can be conveniently loaded for various potential uses, such as validating anomaly detection and data fusion as well as investigating environmental influences on train responses. Nature Publishing Group UK 2019-08-12 /pmc/articles/PMC6690915/ /pubmed/31406119 http://dx.doi.org/10.1038/s41597-019-0148-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Liu, Jingxiao Chen, Siheng Lederman, George Kramer, David B. Noh, Hae Young Bielak, Jacobo Garrett, James H. Kovačević, Jelena Bergés, Mario Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh |
title | Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh |
title_full | Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh |
title_fullStr | Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh |
title_full_unstemmed | Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh |
title_short | Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh |
title_sort | dynamic responses, gps positions and environmental conditions of two light rail vehicles in pittsburgh |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6690915/ https://www.ncbi.nlm.nih.gov/pubmed/31406119 http://dx.doi.org/10.1038/s41597-019-0148-9 |
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