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In-service railway track condition monitoring by analysis of axle box accelerations for small to mid-size infrastructure operators

Groos, Jörn Christoffer and Havrila, Patrik and Schubert, Lucas Andreas (2017) In-service railway track condition monitoring by analysis of axle box accelerations for small to mid-size infrastructure operators. In: 1st World Congress on Condition Monitoring 2017, WCCM 2017. WCCM 2017 - 1st World Congress on Condition Monitoring, 13.-16.06.2017, London. ISBN 978-090313264-8.

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About 50% of life-cycle-cost of railway tracks are caused by maintenance actions which are nowadays typically conducted within corrective maintenance schemes. The accelerating digitalization and development of low-cost sensors provide the chance especially for small infrastructure operators to introduce cost-effective track condition monitoring on a daily basis utilizing embedded sensors on their in-service vehicles. This will allow the challenging step forward from reactive corrections to proactive preventive maintenance actions to significantly reduce maintenance cost. We present the overall framework and first results of a prototype implementation of the complete system for quasi-continuous condition monitoring regarding short-wavelength (a few centimetre to a few meter) defects of railway tracks such as rail corrugation from the embedded sensor to the visualized data analysis result. We gather georeferenced triaxial axle box accelerations in the frequency range from 0.8 Hz to 8000 Hz by a prototype measurement system on a shunter locomotive operating on the railway network of Braunschweig inland harbour in Germany (total track length about 15 km). The prototype implementation in operational environment provides data of up to now four months of shunting operation to develop and evaluate data analysis algorithms. The acceleration sensor data is combined with further relevant data such as the digital map of the railway infrastructure and other operational data to be prepared for data analysis by our prototype implementation of a land-side data management system. We present results of the land-side data analysis chain including the track-selective georeferencing by multi-sensor-fusion, the extraction of relevant features from the axle box acceleration data for pattern recognition and the further intelligent data analysis to provide spatiotemporal information about track conditions. The obtained results are finally visualized for the infrastructure operator by the data management web-frontend.

Item URL in elib:https://elib.dlr.de/123161/
Document Type:Conference or Workshop Item (Speech)
Title:In-service railway track condition monitoring by analysis of axle box accelerations for small to mid-size infrastructure operators
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Groos, Jörn ChristofferUNSPECIFIEDhttps://orcid.org/0000-0003-3871-0756
Schubert, Lucas AndreasUNSPECIFIEDhttps://orcid.org/0000-0002-5516-5326
Date:13 June 2017
Journal or Publication Title:1st World Congress on Condition Monitoring 2017, WCCM 2017
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Keywords:Corrective maintenance, Data analysis algorithms, Data management system, Intelligent data analysis, Operational environment, railway infrastructure
Event Title:WCCM 2017 - 1st World Congress on Condition Monitoring
Event Location:London
Event Type:international Conference
Event Dates:13.-16.06.2017
Organizer:International Society for Condition Monitoring (ISCM) and the British Institute of Non-Destructive Testing (BINDT)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - TrackScan (old)
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems
Institute of Transportation Systems > Railway System
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Deposited By: Groos, Jörn Christoffer
Deposited On:16 Nov 2018 07:55
Last Modified:16 Nov 2018 07:55

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