The Iron Ore Line (Malmbanan) is a 473 km long track section located in northern Sweden and has been in operation since 1903. This track section stretches through two countries, namely Sweden and Norway, and the main part of the track runs on the Swedish side, where the owner is the Swedish Government and the infrastructure manager is Trafikverket (the Swedish Transport Administration). The ore trains are owned and managed by the freight operator and mining company LKAB. Due to the high axle load exerted by transportation of the iron ore, 30 tonnes, and the high demand for a constant flow of ore and pellets, the track and wagons must be monitored and maintained on a regular basis. The condition of the wagon wheel is one of the most important aspects in this connection, and here the wheel profile plays an important role. For this reason an automatic laser-based wheel profile monitoring system (WPMS) has been installed on this line using a system lifecycle approach that is based on the reliability, availability, maintainability and safety (RAMS) approach for railways. The system was prepared and installed and is being operated in a collaborative project between the freight operator and infrastructure manager. The measurements are used to diagnose the condition of the wheels, and to further optimize their maintenance. This paper presents a study of the concepts and ideas of the WPMS, and the selection, installation and validation of the equipment using a system lifecycle approach that is based on RAMS for railways. Results from the profile measurements and validation are shown. The system’s reliability during performance in extreme climate conditions, with severe cold and large quantities of snow, is presented. Then the benefits, perceived challenges and acquired knowledge of the system are discussed, and an improved V-model for the lifecycle approach is presented.
[1]
Uday Kumar,et al.
Holistic procedure for rail maintenance in Sweden
,
2008
.
[2]
Ulla Juntti.
Impact of climate on railway operation : a Swedish case study
,
2012
.
[3]
B. D. Ollier.
Intelligent infrastructure - the business challenge
,
2006
.
[4]
Christer Stenström,et al.
Maintenance performance measurement of railway infrastructure with focus on the Swedish network
,
2012
.
[5]
Ingrid Bouwer Utne,et al.
A structured approach to improved condition monitoring
,
2012
.
[6]
Mikael Palo.
Condition monitoring of railway vehicles : a study on wheel condition for heavy haul rolling stock
,
2012
.
[7]
Wing Kong Chiu,et al.
Structural Health Monitoring in the Railway Industry: A Review
,
2005
.
[8]
W Partington.
SEMINAR ON PERMANENT WAY DEVELOPMENTS. WHEEL IMPACT LOAD MONITORING. TECHNICAL NOTE.
,
1993
.
[9]
Barrie Brickle,et al.
Identification of Existing and New Technologies for Wheelset Condition Monitoring
,
2008
.
[10]
Rolf Dach,et al.
Technical Report 2012
,
2013
.
[11]
R D Fröhling,et al.
Wheel-Rail Interface Management: A Rolling Stock Perspective
,
2010
.