Improving the dependability of DC point machines with a novel condition monitoring system

This paper develops a new approach for fault detection and diagnosis for electric direct current (DC) point machines operated on the railways in the UK. It is shown that the electric current is an appropriate parameter to acquire and analyse for DC point machine condition monitoring. The new methodology for fault detection and diagnosis proposed in this paper utilises wavelet transforms and support vector machines. It is shown that this method can detect and diagnose faults to a high degree of accuracy and can provide an indication of the severity of the faults.

• Record URL:
  • https://doi.org/10.1177/0954409713481748
• Record URL:
  • http://pif.sagepub.com/cgi/content/abstract/227/4/322
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09544097
• Supplemental Notes:
  • Reprinted by permission of Sage Publications, Ltd.
• Authors:
  • Asada, Tomotsugu
  • Roberts, Clive
• Publication Date: 2013-7

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 322-332
• Serial:
  • Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
  • Volume: 227
  • Issue Number: 4
  • Publisher: Sage Publications Limited
  • ISSN: 0954-4097
  • EISSN: 2041-3017
  • Serial URL: http://pif.sagepub.com/content/current

Subject/Index Terms

• TRT Terms: Direct current; Fault monitoring; Monitoring; Wavelets
• Identifier Terms: Condition Monitoring for Railway Applications (COMORAN)
• Uncontrolled Terms: Railroad point machines; Support vector machines
• Subject Areas: Maintenance and Preservation; Railroads; Vehicles and Equipment; I60: Maintenance; I95: Vehicle Inspection;

Filing Info

• Accession Number: 01485367
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 1 2013 9:54AM