Research on Predicting the Tamping Cycle of Heavy Haul Railway for Different Large Machine Tamping Modes
AbstractAn important research direction for heavy haul railway maintenance is to use track condition inspection data. This paper analyses the MTQI (Machine Tamping Quality Index) before and after tamping for different large machine..tamping modes (tamping machine type, single/double tamping, stabilizing vehicle, line type) using inspection and repair data and establishes a tamping effect model. A prediction model of the MTQI index using gross weight is established with grey GM (1, 1) prediction technology. When combined with the tamping effect model, it can be used to compare and select maintenance modes and predict the tamping cycle under different tamping modes. Using an example from a heavy haul railway, the paper shows the proposed prediction model will help the track management department select the best tamping maintenance mode. It can provide a scientific and economic decision-making plan for tamping maintenance and facilitate preventive maintenance.
Luo Lin, Zhang Geming, Wu Wangqing, Chai Xuesong. Control
of track smoothness of wheel/rail system [M]. Beijing: China
Railway Publishing House, 2006( In Chinese)
Jovanovic S.and Esveld C.:ECOTRACK:'An objective condition-
based Decision Support System for long-term track M&R
Planning directed towards reduction of Life Cycle Costs',7th
International Heavy Haul Conference ,Brisbane, Australia,10-15
Rivier, R.E. & Korpanec, I. 1997. COTRACK: a Tool to reduce
the Life Cycle Costs of the Track, Proceedings of the World
Congress on Railway Research, Vol. B. pp. 289-295, 16-19
November 1997. Florence.
Deng, J.L. 1982. The control problem of grey systems. Systems
and Control Letters 11(5): 285-294.
Liu, S.F. & Yang, Y.J. 2015. Advances in Grey System Research
(2004-2014), Journal of Nanjing University of Aeronautics &
Astronautics 47(1): 1-18.
QU Jian-jun, WANG Wei-dong, TIAN Xin-yu. Research on
Prediction Method of Life Cycle of Track Quality Based on Grey
System Identification [J]. Journal of the China Railway Society,
QU Jian-jun, GAO Liang, TIAN Xin-yu. Study on the Mid &
Long Term Prediction Model of Track Geometry State Based on
the Grey Time-varying Parameters Theory [J]. Journal of the
China Railway Society, 2010, 32(2):55-59.
J.J.Qu,Z.T.Ke, Research on a preventive tamping maintenance
model for heavy haul railway based on inspection data [C],11th
INTERNATIONAL HEAVY HAUL CONFERENCE,490–
,Cape Town (2017).