Citation: | SHEN Gang, MAO Xin, MAO Wen-li, DONG Qiang-qiang, YIN Xiang-qin. Status and future trend of wheel/rail system[J]. Journal of Traffic and Transportation Engineering, 2022, 22(1): 42-57. doi: 10.19818/j.cnki.1671-1637.2022.01.003 |
[1] |
沈钢, 钟晓波. 铁路车轮踏面外形的逆向设计方法[J]. 机械工程学报, 2010, 46(16): 41-47. https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201016009.htm
SHEN Gang, ZHONG Xiao-bo, Inverse method for design of wheel profiles for railway vehicles[J]. Journal of Mechanical Engineering, 2010, 46(16): 41-47. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201016009.htm
|
[2] |
毛鑫, 沈钢. 基于轮径差函数的曲线钢轨打磨廓形设计[J]. 同济大学学报(自然科学版), 2018, 46(2): 253-259. doi: 10.11908/j.issn.0253-374x.2018.02.017
MAO Xin, SHEN Gang. Curved rail grinding profile design based on rolling radii difference function[J]. Journal of Tongji University (Natural Science), 2018, 46(2): 253-259. (in Chinese) doi: 10.11908/j.issn.0253-374x.2018.02.017
|
[3] |
周清跃, 刘丰收, 张银花, 等. 高速铁路轮轨匹配存在问题及对策[J]. 中国铁道科学, 2017, 38(5): 78-84. doi: 10.3969/j.issn.1001-4632.2017.05.11
ZHOU Qing-yue, LIU Feng-shou, ZHANG Yin-hua, et al. Solutions for problems at wheel-rail interface in high speed railway[J]. China Railway Science, 2017, 38(5): 78-84. (in Chinese) doi: 10.3969/j.issn.1001-4632.2017.05.11
|
[4] |
王令朝. 轮轨润滑技术及应用分析[J]. 现代城市轨道交通, 2020(5): 92-95. https://www.cnki.com.cn/Article/CJFDTOTAL-XDGD202005022.htm
WANG Ling-chao. Wheel rail lubrication technology and application analysis[J]. Modern Urban Transit, 2020(5): 92-95. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XDGD202005022.htm
|
[5] |
TEMPLE P D, HARMON M. LEWIS R, et al. Optimisation of grease application to railway tracks[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2018, 232(5): 1514-1527. doi: 10.1177/0954409717734681
|
[6] |
黄立, 曾京, 李大地, 等. 高速动车组晃车现象的主动控制[J]. 机械, 2019, 46(9): 7-10, 69. https://www.cnki.com.cn/Article/CJFDTOTAL-MECH201909003.htm
HUANG Li, ZENG Jing, LI Da-di, et al. Active control for coach shaking of high-speed EMU[J]. Machinery, 2019, 46(9): 7-10, 69. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-MECH201909003.htm
|
[7] |
UYULAN C, GOKASAN M, SETA BOGOSYAN S. Hunting stability and derailment analysis of the high-speed railway vehicle moving on curved tracks[J]. International Journal of Heavy Vehicle Systems, 2019, 26(6): 824-853. doi: 10.1504/IJHVS.2019.102685
|
[8] |
WANG Shu-shu, SHEN Xiao-meng, TU Xiao-jian. A novel energy-harvesting active radial bogie for railway vehicles: design, simulation and HIL test[J]. Applied Mechanics and Materials, 2015, 733: 695-698. doi: 10.4028/www.scientific.net/AMM.733.695
|
[9] |
MATSUMOTO A, SATO Y, OHNO H, et al. Curving performance evaluation for active-bogie-steering bogie with multibody dynamics simulation and experiment on test stand[J]. Vehicle System Dynamics, 2008, 46(S1): 191-199.
|
[10] |
罗湘萍, 田师峤. 主副构架铰接的主动径向转向架曲线通过性能研究[J]. 城市轨道交通研究, 2016, 19(12): 1-5. https://www.cnki.com.cn/Article/CJFDTOTAL-GDJT201612003.htm
LUO Xiang-ping, TIAN Shi-qiao. Curving performance of active radial bogie with main frame and sub-frame[J]. Urban Mass Transit, 2016, 19(12): 1-5. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GDJT201612003.htm
|
[11] |
DI GIALLEONARDO E, CAZZULANI G, STEFANO MELZI S, et al. The effect of train composition on the running safety of low-flatcar wagons in braking and curving manoeuvres[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2017, 231(6): 666-677. doi: 10.1177/0954409716636923
|
[12] |
尧辉明, 沈钢, 高利君. 基于试验验证的磨耗型钢轨波磨形成机理[J]. 同济大学学报(自然科学版), 2018, 46(10): 1427-1432. doi: 10.11908/j.issn.0253-374x.2018.10.015
YAO Hui-ming, SHEN Gang, GAO Li-jun. Formation mechanism of worn profile rail corrugation based on experimental verification[J]. Journal of Tongji University (Natural Science), 2018, 46(10): 1427-1432. (in Chinese) doi: 10.11908/j.issn.0253-374x.2018.10.015
|
[13] |
GRASSIE S L, KALOUSEK J. Rail corrugation: characteristics, causes and treatments[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2009, 223(6): 581-596. doi: 10.1243/09544097JRRT264
|
[14] |
DANG VAN K D, MAITOURNAM M H, MOUMNI Z, et al. A comprehensive approach for modeling fatigue and fracture of rails[J]. Engineering Fracture Mechanics, 2009, 76(17): 2626-2636. doi: 10.1016/j.engfracmech.2008.12.020
|
[15] |
钟晓波, 沈钢. 高速列车车轮踏面外形优化设计[J]. 同济大学学报(自然科学版), 2011, 39(5): 710-715. doi: 10.3969/j.issn.0253-374x.2011.05.015
ZHONG Xiao-bo, SHEN Gang. Optimization for high-speed wheel profiles[J]. Journal of Tongji University (Natural Science), 2011, 39(5): 710-715. (in Chinese) doi: 10.3969/j.issn.0253-374x.2011.05.015
|
[16] |
SHEN Gang, ZHONG Xiao-bo. A design method for wheel profiles according to the rolling radius difference function[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2011, 225(5): 457-462. doi: 10.1177/2041301710394920
|
[17] |
沈钢, 钟晓波. 铁路车轮踏面外形的逆向设计方法[J]. 机械工程学报, 2010, 46(16): 41-47. https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201016009.htm
SHEN Gang, ZHONG Xiao-bo. Inverse method for design of wheel profiles for railway vehicles[J]. Journal of Mechanical Engineering, 2010, 46(16): 41-47. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201016009.htm
|
[18] |
叶志森, 沈钢. 独立轮踏面外形的设计[J]. 铁道车辆, 2003, 41(1): 19-21. doi: 10.3969/j.issn.1002-7602.2003.01.006
YE Zhi-sen, SHEN Gang. Design of independently rotating wheel tread shape[J]. Journal of Rolling Stock, 2003, 41(1): 19-21. (in Chinese) doi: 10.3969/j.issn.1002-7602.2003.01.006
|
[19] |
MAO Xin, SHEN Gang. A design method for rail profiles based on the geometric characteristics of wheel-rail contact[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2018, 232(5): 1255-1265. doi: 10.1177/0954409717720346
|
[20] |
MAO Xin, SHEN Gang. An inverse design method for rail grinding profiles[J]. Vehicle System Dynamics, 2017, 55(7): 1029-1044. doi: 10.1080/00423114.2017.1296168
|
[21] |
徐凯, 李芾, 李东宇, 等. 动车组的轮轨型面匹配关系[J]. 西南交通大学学报, 2017, 52(2): 389-399. doi: 10.3969/j.issn.0258-2724.2017.02.024
XU Kai, LI Fu, LI Dong-yu, et al. Wheel-rail profile matching relationship of EMU train[J]. Journal of Southwest Jiaotong University, 2017, 52(2): 389-399. (in Chinese) doi: 10.3969/j.issn.0258-2724.2017.02.024
|
[22] |
SAWLEY K, WU Hui-min. The formation of hollow-worn wheels and their effect on wheel/rail interaction[J]. Wear, 2005, 258(7/8): 1179-1186.
|
[23] |
张斌, 付秀琴. 铁路车轮、轮箍踏面剥离的类型及形成机理[J]. 中国铁道科学, 2001, 22(2): 76-81. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTK200102010.htm
ZHANG Bin, FU Xiu-qin. Type and formation mechanism of railway wheel and tire tread spall[J]. China Railway Science, 2001, 22(2): 76-81. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTK200102010.htm
|
[24] |
ZHAO Xin, WEN Ze-feng, ZHU Min-hao, et al. A study on high-speed rolling contact between a wheel and a contaminated rail[J]. Vehicle System Dynamics, 2014, 52(10): 1270-1287. doi: 10.1080/00423114.2014.934845
|
[25] |
张洪. 准高速客车转向架轮缘磨耗原因及改进措施[J]. 铁道车辆, 2000, 38(5): 8-11, 1. doi: 10.3969/j.issn.1002-7602.2000.05.003
ZHANG Hong. Causes to the wheel flange wear on quasi-high speed passenger car bogies and the improvement measures[J]. Journal of Rolling Stock, 2000, 38(5): 8-11, 1. (in Chinese) doi: 10.3969/j.issn.1002-7602.2000.05.003
|
[26] |
XIAO Qian, LUO Zhi-xiang, XU Xu, et al. Research on influence of harmonic wear wheel on wheel/rail contact geometry of high-speed train[J]. Journal of Mechanical Science and Technology, 2019, 33(2): 537-544. doi: 10.1007/s12206-019-0107-6
|
[27] |
JENDEL T. Prediction of wheel profile wear—comparisons with field measurements[J]. Wear, 2002, 253(1/2): 89-99.
|
[28] |
周宇, 张杰, 王少锋, 等. 考虑磨耗的钢轨疲劳裂纹萌生寿命预测仿真[J]. 铁道学报, 2016, 38(7): 91-97. doi: 10.3969/j.issn.1001-8360.2016.07.013
ZHOU Yu, ZHANG Jie, WANG Shao-feng, et al. Simulation on rail head crack Initiation life prediction considering rail wear[J]. Journal of the China Railway Society, 2016, 38(7): 91-97. (in Chinese) doi: 10.3969/j.issn.1001-8360.2016.07.013
|
[29] |
周清跃, 张建峰, 郭战伟, 等. 重载铁路钢轨的伤损及预防对策研究[J]. 中国铁道科学, 2010, 31(1): 27-31. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTK201001007.htm
ZHOU Qing-yue, ZHANG Jian-feng, GUO Zhan-wei, et al. Research on the rail damages and the preventive countermeasures in heavy haul railways[J]. China Railway Science, 2010, 31(1): 27-31. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTK201001007.htm
|
[30] |
CANNON D F, EDEL K O, GRASSIE S, et al. Rail defects: an overview[J]. Fatigue and Fracture of Engineering Materials and Structures, 2003, 26(10): 865-886. doi: 10.1046/j.1460-2695.2003.00693.x
|
[31] |
YOU R L, GOTO K. NGAMKHANONG C, et al. Nonlinear finite element analysis for structural capacity of railway prestressed concrete sleepers with rail seat abrasion[J]. Engineering Failure Analysis, 2019, 95: 47-65. doi: 10.1016/j.engfailanal.2018.08.026
|
[32] |
董孝卿, 朱韶光, 钱卿, 等. LMD车轮外形的直径旋修量影响因素及对应措施研究[J]. 铁道机车车辆, 2017, 37(5): 12-16. doi: 10.3969/j.issn.1008-7842.2017.05.03
DONG Xiao-qing, ZHU Shao-guang, QIAN Qing, et al. Analysis of reprofiling strategy for the LMD wheel tread profile[J]. Railway Locomotive and Car, 2017, 37(5): 12-16. (in Chinese) doi: 10.3969/j.issn.1008-7842.2017.05.03
|
[33] |
龚继军, 郭猛刚, 侯博, 等. 钢轨打磨技术发展现状及打磨策略探讨[J]. 机车电传动, 2020(3): 23-29, 34. https://www.cnki.com.cn/Article/CJFDTOTAL-JCDC202003006.htm
GONG Ji-jun, GUO Meng-gang, HOU Bo, et al. Discussion on rail grinding technology development situation and grind strategies[J]. Electric Drive for Locomotives, 2020(3): 23-29, 34. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JCDC202003006.htm
|
[34] |
刘彦军, 杨涛存, 武威, 等. 基于大数据技术的高铁运营安全规律分析系统设计与应用[J]. 中国铁路, 2020(9): 28-33. https://www.cnki.com.cn/Article/CJFDTOTAL-TLZG202009005.htm
LIU Yan-jun, YANG Tao-cun, WU Wei, et al. Design and application of safety rules analysis system for high speed railway operation based on big data technology[J]. China Railway, 2020(9): 28-33. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TLZG202009005.htm
|
[35] |
张振先, 谭江, 黄双超, 等. 复杂运行环境下高速轮轨最佳撒砂增黏策略试验[J]. 中国铁道科学, 2020, 41(2): 123-130. doi: 10.3969/j.issn.1001-4632.2020.02.15
ZHANG Zhen-xian, TAN Jiang, HUANG Shuang-chao, et al. Experimental study on optimum sanding and adhesion enhancement strategy for high speed wheel and rail under complicated operation environments[J]. China Railway Science, 2020, 41(2): 123-130. (in Chinese) doi: 10.3969/j.issn.1001-4632.2020.02.15
|
[36] |
吴兵, 温泽峰, 王衡禹, 等. 高速轮轨黏着特性影响因素研究[J]. 铁道学报, 2013, 35(3): 18-22. doi: 10.3969/j.issn.1001-8360.2013.03.003
WU Bing, WEN Ze-feng, WANG Heng-yu, et al. Study on factors affecting high-speed wheel-rail adhesion characteristics[J]. Journal of the China Railway Society, 2013, 35(3): 18-22. (in Chinese) doi: 10.3969/j.issn.1001-8360.2013.03.003
|
[37] |
WANG Sheng-chun, LUO Si-wei, HUANG Ya-ping, et al. Railroad online: acquiring and visualizing route panoramas of rail scenes[J]. The Visual Computer, 2014, 30(9): 1045-1057. doi: 10.1007/s00371-013-0911-4
|
[38] |
邹文俊. 钢轨打磨技术及磨具研究进展[J]. 金刚石与磨料磨具工程, 2020, 40(2): 1-4. https://www.cnki.com.cn/Article/CJFDTOTAL-JGSM202002001.htm
ZOU Wen-jun. Research progress of rail grinding technology and abrasives[J]. Diamond and Abrasives Engineering, 2020, 40(2): 1-4. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JGSM202002001.htm
|
[39] |
WANG Meng-Jie, WANG Xi-fu, ZHANG Wen-ying, et al. Research on the special railway intelligence transportation hierarchy and system integration methodology[J]. Sensors and Transducers, 2013, 152(5): 89-97.
|
[40] |
谢佳奇, 朱家诚, 魏俊杰, 等. 铁路牵引变电所智能巡检机器人的研制[J]. 机床与液压, 2020, 48(15): 12-16. doi: 10.3969/j.issn.1001-3881.2020.15.003
XIE Jia-qi, ZHU Jia-cheng, WEI Jun-jie, et al. Development of intelligent inspection robot for railway traction substation[J]. Machine Tool and Hydraulics, 2020, 48(15): 12-16. (in Chinese) doi: 10.3969/j.issn.1001-3881.2020.15.003
|
[41] |
YANG Yun-fan, LING Liang, WANG Chao, et al. Wheel/rail dynamic interaction induced by polygonal wear of locomotive wheels[J]. Vehicle System Dynamics, 2022, 60(1): 211-235. doi: 10.1080/00423114.2020.1807572
|
[42] |
LEE H W. Generation of airborne wear particles from the wheel-rail contact under wet conditions using a twin-disk rig[J]. Wear, 2020, 448/449: 203236. doi: 10.1016/j.wear.2020.203236
|
[43] |
SUN Qi, CHEN Chun-jun, KEMP A H, et al. An on-board detection framework for polygon wear of railway wheel based on vibration acceleration of axle-box[J]. Mechanical Systems and Signal Processing, 2021, 153: 107540. doi: 10.1016/j.ymssp.2020.107540
|
[44] |
SONG Ying, SUN B C. Recognition of wheel polygon based on W/R force measurement by piezoelectric sensors in GSM-R network[J]. Wireless Personal Communications, 2018, 102(2): 1283-1291. doi: 10.1007/s11277-017-5194-z
|
[45] |
PENG Bo, IWNICKI S, SHACKLETON P, et al. Comparison of wear models for simulation of railway wheel polygonization[J]. Wear, 2019, 436/437: 203010. doi: 10.1016/j.wear.2019.203010
|
[46] |
CHI Zhe-xiang, LIN Jing, CHEN Ruo-ran, et al. Data-driven approach to study the polygonization of high-speed railway train wheel-sets using field data of China's HSR train[J]. Measurement, 2020, 149: 107022. doi: 10.1016/j.measurement.2019.107022
|
[47] |
PENG Bo, IWNICKI S, SHACKLETON P, et al. General conditions for railway wheel polygonal wear to evolve[J]. Vehicle System Dynamics, 2021, 59(4): 568-587. doi: 10.1080/00423114.2019.1697458
|
[48] |
WANG Jian, LUO Long-fu, YE Wei, et al. A defect-detection method of split pins in the catenary fastening devices of high-speed railway based on deep learning[J]. IEEE Transactions on Instrumentation and Measurement, 2020, 69(12): 9517-9525. doi: 10.1109/TIM.2020.3006324
|
[49] |
ALAWAD H, KAEWUNRUEN S. AN Min. A deep learning approach towards railway safety risk assessment[J]. IEEE Access, 2020, 8: 102811-102832. doi: 10.1109/ACCESS.2020.2997946
|
[50] |
WEI Xiu-kun, YANG Zi-ming, LIU Yu-xin, et al. Railway track fastener defect detection based on image processing and deep learning techniques: a comparative study[J]. Engineering Applications of Artificial Intelligence, 2019, 80: 66-81. doi: 10.1016/j.engappai.2019.01.008
|
[51] |
MA Shuai, GAO Liang, LIU Xiu-bo, et al. Deep learning for track quality evaluation of high-speed railway based on vehicle-body vibration prediction[J]. IEEE Access, 2019, 7: 185099-185107. doi: 10.1109/ACCESS.2019.2960537
|
[52] |
PING Huang, WEN Chao, FU Li-ping, et al. A deep learning approach for multi-attribute data: a study of train delay prediction in railway systems[J]. Information Sciences, 2020, 516: 234-253. doi: 10.1016/j.ins.2019.12.053
|
[53] |
RAGEH A, EFTEKHAR AZAM S, LINZELL D G. Steel railway bridge fatigue damage detection using numerical models and machine learning: mitigating influence of modeling uncertainty[J]. International Journal of Fatigue, 2020, 134: 105458. doi: 10.1016/j.ijfatigue.2019.105458
|
[54] |
HUANG Xiao-ya, WANG Hao, XUE Wei-hua, et al. Study on time-temperature-transformation diagrams of stainless steel using machine-learning approach[J]. Computational Materials Science, 2020, 171: 109282. doi: 10.1016/j.commatsci.2019.109282
|
[55] |
NADARAJAH N, SHAMDANI A, HARDIE G, et al. Prediction of railway vehicles' dynamic behavior with machine learning algorithms[J]. Electronic Journal of Structural Engineering, 2018, 18(1): 38-46.
|
[56] |
GROSSONI I, HUGHES P, BEZIN Y, et al. Observed failures at railway turnouts: failure analysis, possible causes and links to current and future research[J]. Engineering Failure Analysis, 2021, 119: 104987. doi: 10.1016/j.engfailanal.2020.104987
|
[57] |
JING Guo-qing, SIAHKOUHI M, EDWARDS J R, et al. Smart railway sleepers—a review of recent developments, challenges, and future prospects[J]. Construction and Building Materials, 2021, 271: 121533.
|
[58] |
SERRANO-JIMÉNEZ D, ABRAHAMSSON L, CASTAÑO-SOLÍS S, et al. Electrical railway power supply systems: current situation and future trends[J]. International Journal of Electrical Power and Energy Systems, 2017, 92: 181-192.
|
[59] |
VAGNOLI M, REMENYTE-PRESCOTT R, ANDREWS J. Railway bridge structural health monitoring and fault detection: state-of-the-art methods and future challenges[J]. Structural Health Monitoring, 2018, 17(4): 971-1007.
|
[60] |
ROTHBAUM D. 5G for the future railway mobile communication system[J]. ITU News, 2019, 2019(4): 49-52.
|