Decision support tool based on multi-source data analysis for the tram wheel-rail interface

Wei Xie, Alfredo Nunez, Ron Maas, Zili Li

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

1 Citation (Scopus)
9 Downloads (Pure)

Abstract

This paper presents a methodology to support decision making based on the tram wheel-rail interface condition. The methodology relies on the following measurements: tram failure log-files regarding wheel-sliding events, monitored acoustics data and open source weather information. The proposed methodology consists of three stages: 1) data collection and pre-processing, 2) spatial analysis based on clustering, and 3) decision support based on the extracted information. For clustering, the Density-Based Algorithm (DBSCAN) is used for the analysis of wheel-sliding events. Self-organizing maps (SOMs) are employed for the analysis of acoustics data. A real-life case study is used to show how use of the methodology can find interesting hotspots that are candidates for further monitoring and maintenance actions. The measurements were obtained from the tram system in the city of Rotterdam, The Netherlands.
Original languageEnglish
Title of host publicationProceedings of 15th IFAC Symposium on Control in Transportation Systems (CTS 2018)
Subtitle of host publicationSavona, Italy, June 6-8, 2018
EditorsBart De Schutter , Antonella Ferrara
PublisherElsevier
Pages118-123
Number of pages6
Volume59
Edition9
DOIs
Publication statusPublished - 2018
Event15th IFAC Symposium on Control in Transportation Systems - Savona, Italy
Duration: 6 Jun 20188 Jun 2018
Conference number: 15
http://www.cts2018.unige.it/

Publication series

NameIFAC-PapersOnLine
PublisherElsevier
Number9
Volume51
ISSN (Print)2405-8963

Conference

Conference15th IFAC Symposium on Control in Transportation Systems
Abbreviated titleCTS 2018
CountryItaly
CitySavona
Period6/06/188/06/18
Internet address

Keywords

  • Decision support systems
  • wheel-rail interface
  • tram infra maintenance
  • self-organizing maps
  • density-based clustering

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