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Automatic Condition Monitoring of Railway Overhead Lines from Close-Range Aerial Images and Video Data

Andert, Franz and Kornfeld, Nils and Nikodem, Florian and Li, Haiyan and Kluckner, Stefan and Gruber, Laura and Kaiser, Christian (2020) Automatic Condition Monitoring of Railway Overhead Lines from Close-Range Aerial Images and Video Data. In: 2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020, pp. 1270-1277. International Conference on Unmanned Aircraft Systems, 2020-09-01 - 2020-09-04, Athen, Griechenland. doi: 10.1109/ICUAS48674.2020.9213972. ISBN 978-1-72814-278-4.

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This paper is about automated condition monitoring of critical railway infrastructure using unmanned aircraft systems as flying sensors. As far as possible, automation shall include flight guidance and management as well as automated processing of large sensor data sets. Since a commercial solution must consider the regulatory framework on remotely piloted aircraft systems, the paper discusses legal issues to make allowance for flights beyond visual line of sight. The work described here is focused on Europe and Germany, however, the major principles are likely to be adaptable to other countries. Next to that, the paper presents a strategy for automated image and video data processing. It consists of a super-resolution approach where onboard video camera data from typical offthe-shelf drones can replace higher-resolution still imagery and thus avoid the necessity to use special flight systems, and a deeplearning approach where specific elements are to be detected in the images. With data from flight tests over railway overhead lines, the paper shows an automated detection of rod insulators. Moreover, it presents resolution improvements from video data so that off-the-shelf camera drones can be qualified for the detection of small defects.

Item URL in elib:https://elib.dlr.de/135780/
Document Type:Conference or Workshop Item (Speech)
Title:Automatic Condition Monitoring of Railway Overhead Lines from Close-Range Aerial Images and Video Data
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Andert, FranzUNSPECIFIEDhttps://orcid.org/0000-0002-1638-7735UNSPECIFIED
Kornfeld, NilsUNSPECIFIEDhttps://orcid.org/0000-0003-4889-363XUNSPECIFIED
Date:4 September 2020
Journal or Publication Title:2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1270-1277
Keywords:Predictive Maintenance, Unmanned Aircraft, UAV, UAS, Railway Infrastructure, Deep Learning, Artificial Intelligence, Image Super-Resolution
Event Title:International Conference on Unmanned Aircraft Systems
Event Location:Athen, Griechenland
Event Type:international Conference
Event Start Date:1 September 2020
Event End Date:4 September 2020
Organizer:ICUAS Association
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Rail Transport
DLR - Research area:Transport
DLR - Program:V SC Schienenverkehr
DLR - Research theme (Project):V - Digitalisierung und Automatisierung des Bahnsystems (old), L - The Smart Rotorcraft (old)
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems > Data Management and Knowledge Discovery
Institute of Flight Systems > Safety Critical Systems&Systems Engineering
Deposited By: Andert, Dr.-Ing. Franz
Deposited On:01 Sep 2020 12:19
Last Modified:24 Apr 2024 20:38

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