| 基于随机模型的动车组制动模块稳健优化设计 |
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| 引用本文： | 殷浩,李永华,杜江.基于随机模型的动车组制动模块稳健优化设计[J].机械与电子,2020,38(10):3-7. |
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| 作者姓名： | 殷浩 李永华 杜江 |
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| 作者单位： | 大连交通大学机车车辆工程学院，辽宁 大连 116028 |
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| 基金项目： | 科技创新基金;辽宁省高等学校创新团队支持计划;国家自然科学基金;辽宁省教育厅科学研究项目 |
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| 摘 要： | 针对目前产品优化设计中未考虑设计变量随机性和灵敏度指数对产品质量特性的影响及优化求解效率低等问题，提出一种综合考虑灵敏度指数与质量损失函数的稳健优化设计方法。通过假设设计变量的分布类型，得到设计变量的概率分布特征，将设计变量对产品质量特性的灵敏度指数与质量损失函数加权整合，并以此作为优化目标，以设计变量的容差作为约束条件，构建随机稳健优化模型。通过扩大种群数目、改进控制参数及增加惩罚因子的方法对遗传算法进行改进，结合改进的遗传算法对优化模型进行求解，得到优化模型的全局稳健最优解。以某动车组制动模块为例，采用给出的方法对其进行稳健优化设计，验证该方法的有效性与合理性。优化结果表明，该方法能够实现动车组制动模块的稳健优化设计，提高了制动模块的抗干扰能力。
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| 关 键 词： | 制动模块 随机模型 稳健优化 改进遗传算法 |
Robust Optimization Design of Brake Module for EMU Based on the Stochastic Model |
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| YIN Hao,LI Yonghua,DU Jiang.Robust Optimization Design of Brake Module for EMU Based on the Stochastic Model[J].Machinery & Electronics,2020,38(10):3-7. |
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| Authors: | YIN Hao LI Yonghua DU Jiang |
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| Affiliation: | School of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, China |
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| Abstract: | A robust optimization design method, considering sensitivity index and quality loss function, was proposed according to the present design variables randomness and sensitivity index influence on product quality characteristics and low efficiency of optimization. By assuming the distribution types of design variables, the probabilistic distribution characteristics of design variables were obtained, and the sensitivity index of design variables to product quality characteristics and quality loss function were weighted integrated, which was taken as the optimization objective, and the tolerance of design variables as the constraint condition, to build a stochastic robust optimization model. The genetic algorithm was improved by expanding the population number, improving the control parameters and increasing the penalty factor, and the optimization model was solved by combining the improved genetic algorithm to obtain an overall optimal solution model. Taking the brake module of an EMU as an example, the proposed method was used to perform robust optimization design to verify the effectiveness and rationality of the method. The optimization results show that this method can realize the robust optimization design of the EMU brake module and improve the anti-interference ability of the brake module. |
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| Keywords: | brake module stochastic model robust optimization improved genetic algorithm |
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