Multi-Objective Optimization of Rail Pre-Grinding Profile in Straight Line for High Speed Railway
Multi-Objective Optimization of Rail Pre-Grinding Profile in Straight Line for High Speed Railway
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DOI：
10.1007/s12204-018-1974-1
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发表时间：
2018-08
影响因子：
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通讯作者：
W. Zeng;Wen-sheng Qiu;Tao Ren;Wen Sun;Yue Yang
中科院分区：
文献类型：
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作者：
W. Zeng;Wen-sheng Qiu;Tao Ren;Wen Sun;Yue Yang
为了对钢轨磨前轮廓进行平滑修正，采用带权因子的非均匀有理B样条(NURBS)曲线建立了钢轨磨前轮廓的参数化模型。以轮对横向位移量为随机变量，采用拉丁超立方体抽样法和三维弹塑性有限元方法建立了轮轨接触随机有限元模型。计算了具有不同权重因子的不同磨前轮廓中的节点累积接触应力(NACS)和节点平均接触应力(NMCS)的最大值，并以此作为训练样本，建立了两种克立格模型。建立了以NACS模型和NMCS Kriging模型为目标函数的磨前轮廓多目标优化模型。利用非支配排序遗传算法II(NSGA-II)搜索最优权因子，得到相应的最优磨前轮廓。优化前后的接触应力计算表明，优化后的NACS和NMCS的最大值明显下降。
In order to modify the rail pre-grinding profile smoothly, non-uniform rational B-spline (NURBS) curve with weight factors is used to establish a parameterized model of the profile. A wheel-rail contact stochastic finite element model (FEM) is constructed by the Latin hypercube sampling method and 3D elasto-plastic FEM, in which the wheelset’s lateral displacement quantity is regarded as a random variable. The maximum values of nodal accumulated contact stress (NACS) and nodal mean contact stress (NMCS) in different pre-grinding profiles with differential weight factors are calculated and taken as the training samples to establish two Kriging models. A multi-objective optimization model of pre-grinding profile is established, in which the objective functions are the NACS and NMCS Kriging models. The optimum weight factors are sought using a non-dominated sorting genetic algorithm II (NSGA-II), and the corresponding optimum pre-grinding profile is obtained. The contact stress calculation before and after optimization indicates that the maximum values of NACS and NMCS decline significantly.