Improvement of railway ballast maintenance approach, incorporating ballast geometry and fouling conditions

被引:33
|
作者
Sadeghi, J. [1 ]
Motieyan-Najar, M. E. [1 ]
Zakeri, J. A. [1 ]
Yousefi, B. [2 ]
Mollazadeh, M. [1 ]
机构
[1] Iran Univ Sci & Technol, Sch Railway Engn, Tehran 16844, Iran
[2] Geotech & Strength Mat Study Ctr Municipal, Geophys Dept, Tehran, Iran
关键词
Railway; Assessment technique; Quality index; GPR; Ballast; Maintenance planning; GROUND-PENETRATING RADAR; FOULED BALLAST; TRACK; GPR; MODEL; DETERIORATION; INSPECTION;
D O I
10.1016/j.jappgeo.2018.02.020
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Ballast plays an important role in the stability of railway track systems. The effectiveness of the ballast in maintaining the track stability is very much dependent on its mechanical conditions. The available ballast maintenance approaches are mainly based on only track geometry conditions (such as track profile) which do not sufficiently reflect the ballast mechanical behaviors. That is, the ballast potential of degradation (i.e., ballast long term behaviors) has been omitted. This makes the effectiveness of the current ballast maintenance approach questionable, indicating a need for a more comprehensive and effective ballast conditions assessment technique. In response to this need, two ballast condition indices based on ballast geometry degradation (BGI) and the level of ballast fouling (BFI) as the main indicators of ballast mechanical behavior were developed. The BC! is a function of the standard deviations of track alignment, unevenness and twist. The BFI was developed based on the data obtained from the ground penetration radar (GPR). Making use of the new indices, a more reliable maintenance algorithm was developed. Through illustrations of the applicability of the new maintenance algorithm in a railway line, it was shown that the new algorithm causes a considerable improvement in the maintenance effectiveness and an increase in the life cycle of railway tracks by making more effective allocation of resources and more accurate maintenance planning. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:263 / 273
页数:11
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