Carnegie Mellon University
Browse
10.1038s41597-019-0148-9.pdf (5.45 MB)

Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh

Download (5.45 MB)
journal contribution
posted on 2019-10-31, 17:43 authored by Jingxiao LiuJingxiao Liu, Siheng Chen, George Lederman, David B. Kramer, Hae Young NohHae Young Noh, Jacobo BielakJacobo Bielak, James GarrettJames Garrett, Jelena KovacevicJelena Kovacevic, Mario BergesMario Berges
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.

History

Publisher Statement

This is the version of record of Liu, J., Chen, S., Lederman, G. et al. Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh. Sci Data 6, 146 (2019) doi:10.1038/s41597-019-0148-9 This article is licensed under a Creative Commons Attribution 4.0 International License This article is published open access using the Carnegie Mellon University Libraries' Article Processing Charge fund

Date

2019-08-12

Usage metrics

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC