Title: Prediction model with optimal matching parameters for a dynamic track stabiliser during railway maintenance

Authors: Bo Yan; Bin Hu; Yayu Huang

Addresses: Faculty of Art and Communication, Kunming University of Science and Technology, Kunming, 650500, China ' China Railway Construction Heavy Industry Co., Ltd., Changsha, 410100, China ' Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, 650500, China

Abstract: Nowadays, high-speed and heavy duty trains make ballasted track extremely busy, and thus it is necessary to solve the conflict between the traffic density and the maintenance work load. However, since the mechanical properties of discrete ballast bed are complex, there is a lack of in-depth investigation into the working performance of large-scale railroad maintenance machinery. In this paper, we take the WD-320 dynamic track stabiliser as the research object, to study the effect of operation parameters on the quality state of the ballast bed. Based on the field test data, a prediction model for optimal matching of operation parameters has been constructed, which can be used to estimate, compare and determine the optimal operation parameter combination for the operation process. By operating according to the optimal operation parameter combination, the optimum quality state of the ballast bed can be quickly reached, to solve the conflict between the traffic density and the necessary maintenance window.

Keywords: dynamic track stabiliser; the sleeper lateral resistance; operation parameters; optimal matching; prediction model; ballast state correction coefficient; railway maintenance; the optimum quality state of ballast bed; fitting analysis.

DOI: 10.1504/IJMIC.2019.107485

International Journal of Modelling, Identification and Control, 2019 Vol.33 No.4, pp.369 - 377

Received: 29 Nov 2019
Accepted: 12 Dec 2019
Published online: 29 May 2020 *

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