| 考虑打磨量的重载钢轨打磨廓形优化设计 |
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| 引用本文： | 吴磊,康彦兵,董勇,张华鹏.考虑打磨量的重载钢轨打磨廓形优化设计[J].西南交通大学学报,2022,57(4):805-812. |
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| 作者姓名： | 吴磊 康彦兵 董勇 张华鹏 |
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| 作者单位： | 西南交通大学机械工程学院，四川 成都 610031 |
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| 基金项目： | 国家自然科学基金（51605395）；;四川省科技计划（2020YJ0034,2020JDTD0012,2020YFQ0024,2019YJ0209）； |
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| 摘 要： | 为在重载钢轨打磨廓形优化设计中最小化钢轨打磨量，建立了打磨量的钢轨廓形对齐及计算方法，设计以轮轨磨耗指数、轮轨接触应力以及钢轨打磨量为优化子目标的综合优化评价模型，并对不同优化策略的优化结果进行了分析. 首先，通过矩阵旋转变换、曲线拟合及样条插值等理论建立钢轨廓形自动对齐算法，并计算目标廓形打磨量；其次，考虑轮轨磨耗指数、接触应力以及钢轨打磨量，建立综合优化目标函数，采用遗传算法并联合车辆轨道动力学仿真模型求解优化钢轨打磨廓形；最后，运用所建立的钢轨廓形优化设计模型计算分析不同优化策略的设计结果. 研究结果表明:同时考虑轮轨磨耗、轮轨接触应力和钢轨打磨量，优化后曲线外、内轨廓形平均磨耗指数相比初始廓形下降68.9%，内轨接触应力下降39.1%，打磨量下降21.8%，优化效果最佳；只考虑轮轨磨耗和接触应力时，优化后曲线外轨廓形磨耗指数和内轨接触应力下降较为明显，但打磨量下降速率相对较慢，仅为11.3%；只考虑打磨量时，优化后钢轨廓形打磨量下降最快，为24.4%，但轮轨接触应力显著变大.
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| 关 键 词： | 重载钢轨 打磨量 轮轨磨耗 轮轨接触应力 廓形优化 |
| 收稿时间： | 2021-02-03 |
Optimal Design of Heavy-Haul Rail Grinding Profile Considering Grinding Amount |
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| WU Lei,KANG Yanbing,DONG Yong,ZHANG Huapeng.Optimal Design of Heavy-Haul Rail Grinding Profile Considering Grinding Amount[J].Journal of Southwest Jiaotong University,2022,57(4):805-812. |
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| Authors: | WU Lei KANG Yanbing DONG Yong ZHANG Huapeng |
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| Affiliation: | School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China |
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| Abstract: | In order to minimize grinding amount in optimization design of heavy-haul rail grinding profile, an alignment and calculation method of the grinding amount of rail profile was established. Meanwhile, a comprehensive optimization evaluation model was designed. The model regarded wheel-rail wear index, wheel-rail contact stress and rail grinding amount as optimization sub-objectives, and the optimization results of different optimized strategies were analyzed. Firstly, an automatic alignment algorithm for rail profile was established through the theories of matrix rotation transformation, curve fitting and spline interpolation. Then the amount of rail grinding was calculated. Secondly, considering the optimization indicators such as wheel-rail wear index, contact stress and rail grinding amount, a comprehensive optimization objective function was established. The genetic algorithm was used to solve the optimized rail profile in conjunction with the vehicle track dynamics simulation model. Finally, the design results of different optimization strategies were calculated and analyzed by using the established rail profile optimization design model. The results show that, considering wheel-rail wear, wheel-rail contact stress and amount of rail grinding at the same time, the average wear index of the optimized high and low rail profile reduces by 68.9% when compared with the initial profile. The low rail contact stress obtains a decrease of 39.1%. The grinding amount gets a reduction of 21.8%. Thus the optimized effect is the best. After optimization, the high rail profile wear index and low rail contact stress decrease significantly in conditions of only considering wheel-rail wear and contact stress, but the decline rate of the grinding amount is relatively slow, reaching 11.3%. When only considering the grinding amount, the grinding amount of rail profile drops the fastest after optimization, which is 24.4%, while the wheel-rail contact stress is significantly larger. |
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