Condition monitoring and e-maintenance solution of railway wheels

Projekt:

JVTC

Sammanfattning:
Purpose – The purpose of this paper is to investigate the failure-driven capacity consumption of wheels on the track, to determine whether there are some relations to vehicle wheel configurations that show a larger amount of failures, and to ascertain the influence of the temperature and the travelling direction of the train on the number of events. This information can be used to develop prognostic health management (PHM) so that more track capacity can be gained without modifications, re-building or re-investments.
Design/methodology/approach – This paper presents a study of 1,509 warning and alarm events concerning train wheels. The data come from the infrastructure manager’s wheel defect detectors and wheel profile measurement system. These data have been analysed and processed to find patterns and connections to different vehicles, travelling directions and temperatures.
Findings – Lower temperatures increase the probability of wheels having high vertical forces. Trains with different wheel configurations show different results. With high vertical forces, the probability of wheel failures at axle 6 and 7 is high for locomotives with two bogies and three axles in each bogie (2x3). All these findings can be used to develop the maintenance, monitoring and inspection principles for wheels.
Practical implications – The inspection of wheels to detect failures needs to be more frequent on days and in seasons with lower temperatures. The wheel inspection should be performed more frequently at axle 6 and 7 for locomotives with a 2x3 wheel configuration. The inspection and monitoring of wheels need to be carried out more carefully for trains travelling south, to avoid a large amount of wheels with high force levels rolling in the southern direction.
Originality/value – The analysis carried out in this paper identifies important factors that correlate with the high occurrence of wheel defects. It also proposes a conceptual e-maintenance model for the combination of wheel condition monitoring data from different system. The value of this study is the provision of information to support prognostic and health management system to support proactive maintenance.

Författare: Matthias Asplund ; Stephen Mayowa Famurewa ; Matti Rantatalo
Utgivare: MCB University Press, Emerald
Utgivningsdatum: 2014
Diarienummer: TRV 2011/58769
ISSN: 1355-2511
Antal sidor: 12
Språk: Engelska
Kontaktperson: Per Olof Larsson Kråik, UHjbs