Virtual Reality and Convolutional Neural Networks for Railway Catenary Support Components Monitoring

Wenqiang Liu, Zhigang Liu, Alfredo Nunez

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

5 Citations (Scopus)
38 Downloads (Pure)

Abstract

The development of algorithms for detecting failures in railway catenary support components has, among others, one major challenge: data about healthy components are much more abundant than data about defective components. In this paper, virtual reality technology is employed to control the learning environment of convolutional neural networks (CNNs) for the automatic multicamera-based monitoring of catenary support components. First, 3D image data based on drawings and real-life video images are developed. Then, a virtual reality environment for monitoring the catenary support system is created, emulating real-life conditions such as measurement noise and a multicamera train simulation to resemble state-of-the-art monitoring systems. Then, CNNs are used to extract and fuse the features of multicamera images. Experiments are conducted for monitoring the cantilever support connection, both down (CSC-D) and up (CSC-U), and registration arm support connection, both down (RASC-D) and up (RASC-U). Experimental results show that the CNNs trained in the virtual reality environment can capture the most relevant spatial information of the catenary support components. Multicamera image detection based on CNNs detects screw loss for all four components. For CSC-D and RASC-U, normal and pin-loss images are also fully detected. A challenge remains in increasing the pin-loss detection for both CSC-U and RASC-D.

Original languageEnglish
Title of host publication2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2183-2188
Number of pages6
ISBN (Electronic)9781538670248
DOIs
Publication statusPublished - 2019
Event22nd IEEE International Conference on Intelligent Transportation Systems, ITSC 2019 - Auckland, New Zealand
Duration: 27 Oct 201930 Oct 2019
https://www.itsc2019.org/

Conference

Conference22nd IEEE International Conference on Intelligent Transportation Systems, ITSC 2019
Country/TerritoryNew Zealand
CityAuckland
Period27/10/1930/10/19
Internet address

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Fingerprint

Dive into the research topics of 'Virtual Reality and Convolutional Neural Networks for Railway Catenary Support Components Monitoring'. Together they form a unique fingerprint.

Cite this