Research on Predicting the Tamping Cycle of Heavy Haul Railway for Different Large Machine Tamping Modes.

An 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 decisionmaking plan for tamping maintenance and facilitate preventive maintenance. [ABSTRACT FROM AUTHOR]