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Rail Profile Optimization Method Considering Grinding Deviation
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Bolun AN1, Jin ZHANG1, Fengshou LIU1, Guang YANG1, Ming ZHAI1, Min CHEN2
China Railway Science | 2026, 47(2) : 22 - 32
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China Railway Science | 2026, 47(2): 22-32
Rail Profile Optimization Method Considering Grinding Deviation
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Bolun AN1, Jin ZHANG1, Fengshou LIU1, Guang YANG1, Ming ZHAI1, Min CHEN2
Affiliations
  • 1.Metals and Chemistry Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing100081, China
  • 2.Huai'an High-Speed Railway Infrastructure Section, China Railway Shanghai Group Co., Ltd., Huai'anJiangsu223299, China
Published: 2026-03-01 doi: 10.3969/j.issn.1001-4632.2026.02.03
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To address the problem where the gauge corner of rails is prone to negative deviation due to excessive grinding, leading to reduced wheel-rail equivalent conicity and impaired running stability of Electric Multiple Units (EMUs), a rail profile optimization method considering grinding deviation is proposed. First, taking a high-speed railway as an example, statistical analysis is conducted on the deviation of measured post-grinding rail profiles to reveal the distribution characteristics of grinding deviation, and the adverse effects of negative deviation on wheel-rail contact performance are verified through vehicle dynamics simulation. Second, the measured grinding profiles are divided into training and validation sets. With the deviation between the degraded profile and the 60N profile controlled within -0.2 mm to +0.2 mm and the nominal equivalent conicity no less than 0.034 as constraint conditions, and with the the optimization objective that the contact stress for the optimized profile matched with the LMA wheel not exceed that of the LMA-60N combination, a genetic algorithm is employed to optimize seven characteristic parameters of the 60N profile, yielding the optimized profile and the degraded profile considering negative deviation caused by excessive grinding. Finally, the performance of the optimized and degraded profiles is verified through wheel-rail contact analysis and vehicle dynamics calculation; and a comparative evaluation is conducted against the standard 60N profile and two sets of field-measured grinding profiles. The results show that: in the gauge corner region (16° - 45°), the profile deviation is predominantly negative, mainly distributed in the range of -0.8 mm to 0 mm with a mean value of approximately -0.4 mm, indicating a prominent excessive grinding problem; compared with the standard 60N profile, the optimized profile matched with the LMA wheel achieves an increased nominal equivalent conicity of 0.036 and a 14% reduction in wheel-rail contact stress, exhibits comparable dynamic performance and shows improved car body lateral stability; the deviation between the degraded profile and the 60N profile is controlled within -0.2 mm to +0.2 mm, with a nominal equivalent conicity of 0.034, satisfying the design constraints and effectively resolving the problem of excessively low equivalent conicity; compared with the two sets of field-measured grinding profiles, the degraded profile demonstrates significant advantages in both dynamic and contact mechanical performance, with reductions of 19% in wheelset lateral acceleration, 7% in bogie frame lateral acceleration, and 13% in car body lateral acceleration, as well as reductions of 19% - 37% in maximum normal contact stress and 33% - 41% in maximum tangential contact stress, along with significantly reduced average contact stress and more concentrated distribution. The proposed profile optimization method provides a reference for field grinding operations and offers guidance for addressing the low conicity hunting problem of EMUs.

Rail grinding  /  Rail profile  /  Rail-wheel matching  /  Rail profile deviation  /  Rail profile optimization
Bolun AN, Jin ZHANG, Fengshou LIU, Guang YANG, Ming ZHAI, Min CHEN. Rail Profile Optimization Method Considering Grinding Deviation[J]. China Railway Science, 2026 , 47 (2) : 22 -32 . DOI: 10.3969/j.issn.1001-4632.2026.02.03
Year 2026 volume 47 Issue 2
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doi: 10.3969/j.issn.1001-4632.2026.02.03
  • Receive Date:2025-11-13
  • Online Date:2026-06-03
  • Published:2026-03-01
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  • Received:2025-11-13
  • Revised:2026-01-26
Affiliations
    1.Metals and Chemistry Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing100081, China
    2.Huai'an High-Speed Railway Infrastructure Section, China Railway Shanghai Group Co., Ltd., Huai'anJiangsu223299, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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