Target Profile Optimization of Asymmetrical Grinding for Rail with Sharp-radius Curve
-
摘要: 小半径曲线钢轨非对称打磨能够减少轨头侧磨,增加轮对导向能力,对非对称打磨目标型面优化,能够提高打磨质量,进一步改善轨道车辆通过小半径曲线时的轮轨接触性能和轮对导向能力。利用NURBS曲线构建了基于可调权因子的钢轨非对称打磨区域轨头曲线参数化模型,建立了以轮轨接触性能和轮对曲线通过能力Kriging代理模型为目标函数的非对称打磨目标型面多目标优化模型。采用NSGA-Ⅱ算法对可调权因子进行多目标优化,得到了优化的钢轨非对称打磨目标型面。优化结果表明,车辆的轮轨接触性能和轮对曲线通过能力得到明显改善。
-
关键词:
- 非对称打磨 /
- 小半径曲线 /
- 目标型面优化 /
- 接触应力 /
- Kriging代理模型
Abstract: Asymmetric grinding for rail with sharp-radius curve can reduce rail head side grinding, increase wheelset guiding ability; optimizing the target surface of asymmetric grinding can improve grinding quality and further improve wheel-rail contact stress concentration and wheel-set guiding ability of rail vehicles when passing through sharp-radius curve. Based on NURBS curve, a parametric model of rail head curve in asymmetric grinding area was constructed based on adjustable weight factor, and a multi-objective global optimization model of asymmetric grinding target profile was established based on Kriging surrogate model of wheel-rail contact performance and wheel-pair curve passing ability. With the NSGA-Ⅱ algorithm based on multi-objective global optimization of adjustable power factor, the optimization target profile of the rail asymmetrical grinding is obtained. The optimization results show that the wheel-rail contact stress concentration and the wheel-set curve passing ability of the vehicle are obviously improved. -
表 1 打磨区域可调权因子及其取值范围
序号 可调权因子 当前值 上限 下限 1 w16 1 2 0 2 w17 1 2 0 3 w18 1 2 0 表 2 Kriging代理模型训练样本
序号 w16 w17 w18 非对称打磨性能指标 σ Δr 1 1.952 49 0.541 903 0.318 814 1 921.74 8.813 2 1.308 123 0.232 827 0.142 763 1 980.65 8.947 3 1.183 405 1.680 745 1.809 266 2 097.39 8.251 ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ 29 0.288 095 0.754 156 1.122 051 2 277.86 8.237 30 1.536 933 1.828 776 0.849 437 2 018.11 8.593 表 3 可调权因子初始值与优化结果
可调权因子 初始值 优化结果 w16 1 0.910 w17 1 0.324 w18 1 0.580 -
[1] CUERVO P A, SANTA J F, TORO A. Correlations between wear mechanisms and rail grinding operations in a commercial railroad[J]. Tribology International, 2015, 82: 265-273 doi: 10.1016/j.triboint.2014.06.025 [2] CRAVEN N, BEWES O G, FENECH B A, et al. Responding to the Environmental Noise Directive by demonstrating the benefits of rail grinding on the Great Britain′s railway network[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2013, 227(6): 668-676 doi: 10.1177/0954409713494948 [3] 肖杰灵, 刘学毅. 钢轨非对称廓型的设计方法[J]. 西南交通大学学报, 2010, 45(3): 361-365 doi: 10.3969/j.issn.0258-2724.2010.03.007XIAO J L, LIU X Y. Design method of rail asymmetric silhouette[J]. Journal of Southwest Jiaotong University, 2010, 45(3): 361-365 (in Chinese) doi: 10.3969/j.issn.0258-2724.2010.03.007 [4] SROBA P, MAGEL E, PRAHL F. RT and S: improved profiles need special grinding[J]. Railway Track and Structures, 2004, 100(12): 26-28 http://gateway.proquest.com/openurl?res_dat=xri:pqm&ctx_ver=Z39.88-2004&rfr_id=info:xri/sid:baidu&rft_val_fmt=info:ofi/fmt:kev:mtx:article&genre=article&jtitle=Railway%20Track%20and%20Structures&atitle=Improved%20profiles%20need%20special%20grinding [5] 贾晋中, 司道林. 朔黄铁路小半径曲线轨道钢轨打磨目标型面研究[J]. 中国铁道科学, 2014, 35(4): 15-21 doi: 10.3969/j.issn.1001-4632.2014.04.03JIA J Z, SI D L. Target profile of rail grinding for small radius curve of Shuohuang railway[J]. China Railway Science, 2014, 35(4): 15-21 (in Chinese) doi: 10.3969/j.issn.1001-4632.2014.04.03 [6] DOIH, MIYAMOTO T, FURUKAWA A, et al. A study on relationship between rail grinding and flange climbing of railway vehicle at low speed in curve[J]. Transactions of the Japan Society of Mechanical Engineers Series C, 2011, 77(781): 3325-3336 doi: 10.1299/kikaic.77.3325 [7] 周骏, 刘林芽, 万鹏. 客运专线铁路曲线段钢轨型面优化[J]. 铁道标准设计, 2014, 58(7): 20-23 https://www.cnki.com.cn/Article/CJFDTOTAL-TDBS201407006.htmZHOU J, LIU L Y, WAN P. Optimization of rail profile in curved section of railway passenger dedicated line[J]. Railway Standard Design, 2014, 58(7): 20-23 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TDBS201407006.htm [8] 周清跃, 张银花, 田常海, 等. 60N钢轨的廓型设计及试验研究[J]. 中国铁道科学, 2014, 35(2): 128-135 https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTK201402022.htmZHOU Q Y, ZHANG Y H, TIAN C H, et al. Profile design and test study of 60N rail[J]. China Railway Science, 2014, 35(2): 128-135 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTK201402022.htm [9] ADACHI M, MATSUMOTO A. Improvement of curving performance by expansion of gauge widening and additional measures[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2012, 226(2): 203-215 doi: 10.1177/0954409711408974 [10] ASHOFTEH R S. Calculating the contact stress resulting from lateral movement of the wheel on rail by applying hertz theory[J]. International Journal of Railway, 2013, 6(4): 148-154 doi: 10.7782/IJR.2013.6.4.148 [11] 蔡安江, 杜金健, 宋仁杰, 等. 五轴加工刀具轨迹NURBS插补技术的研究[J]. 机械科学与技术, 2017, 36(3): 402-408 https://www.cnki.com.cn/Article/CJFDTOTAL-JXKX201703013.htmCAI A J, DU J J, SONG R J, et al. Study on NURBS interpolation technology of five-axis machining tool path[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(3): 402-408 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXKX201703013.htm [12] ROSHANIAN J, EBRAHIMI M. Latin hypercube sampling applied to reliability-based multidisciplinary design optimization of a launch vehicle[J]. Aerospace Science and Technology, 2013, 28(1): 297-304 doi: 10.1016/j.ast.2012.11.010 [13] ESPATH L F R, BRAUN A L, AWRUCH A M, et al. NURBS-based three-dimensional analysis of geometrically nonlinear elastic structures[J]. European Journal of Mechanics-A/Solids, 2014, 47: 373-390 doi: 10.1016/j.euromechsol.2014.05.005 [14] LEE J, KIM J. Kriging-based approximate optimization of high-speed train nose shape for reducing micropressure wave[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2007, 221(2): 263-270 doi: 10.1243/0954409JRRT110 [15] ZHU P, PAN F, CHEN W, et al. Lightweight design of vehicle parameters under crashworthiness using conservative surrogates[J]. Computers in Industry, 2013, 64(3): 280-289 doi: 10.1016/j.compind.2012.11.004 [16] BANDYOPADHYAY S, BHATTACHARYA R. Solving multi-objective parallel machine scheduling problem by a modified NSGA-Ⅱ[J]. Applied Mathematical Modelling, 2013, 37(10-11): 6718-6729 http://www.zhangqiaokeyan.com/academic-journal-foreign_other_thesis/0204111583786.html