动车组电机吊架多目标可靠性优化设计

李永华; 李东明; 宫琦; 吴永鑫

doi:10.13433/j.cnki.1003-8728.20200185

动车组电机吊架多目标可靠性优化设计

doi: 10.13433/j.cnki.1003-8728.20200185

大连交通大学机车车辆工程学院，辽宁大连 116028

基金项目:

国家自然科学基金项目 51875073

辽宁省教育厅科学研究项目 JDL2019005

辽宁省高等学校创新团队支持计划 LT2016010

大连市科技创新基金计划 2019J11CY017

详细信息

作者简介:
李永华(1971-), 教授, 博士生导师, 研究方向为车辆结构分析与现代设计方法、车辆结构疲劳可靠性分析, yonghuali@163.com

中图分类号: U271.91
计量
- 文章访问数: 103
- HTML全文浏览量: 40
- PDF下载量: 28
- 被引次数: 0
出版历程
- 收稿日期: 2019-02-22
- 刊出日期: 2021-07-01

Multi-objective Reliability Optimization Design of Motor Hanger for EMU

School of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian 116028, Liaoning, China

摘要

摘要: 为提高高速动车组电机吊架的承载能力，考虑几何参数的随机性，将响应面法和多目标遗传算法相结合对其进行可靠性优化设计。首先，对电机吊架进行静强度和位移灵敏度分析，找出设计变量；其次，对设计变量进行中心组合试验设计，根据试验设计点来拟合静强度和位移的多项式响应面模型；然后，将几何参数的随机性转化为可靠度，运用最小二乘法拟合可靠度函数方程作为约束条件；最后，运用多目标遗传算法对电机吊架进行可靠性优化设计。研究结果表明：响应面法与结构可靠性优化方法相结合，可以简化求解过程，提高优化结果的可靠度。
- 电机吊架 /
- 响应面模型 /
- 可靠性优化 /
- 多目标遗传算法
Abstract: In order to improve the bearing capacity of high-speed electric multiple units (EMU) motor hangers, considering the randomness of geometric parameters, the response surface method is combined with multi-objective genetic algorithm to optimize its reliability. Firstly, the static strength and displacement sensitivity analysis of the motor hanger are finished to find the design variables; secondly, the central combination test design is carried out for the design variables, and the polynomial response surface model of static strength and displacement is fitted according to the test design points; then, the randomness of geometric parameters is transformed into reliability, and the least square method is used to fit the reliability function equation as the constraint condition; finally, the multi-objective genetic algorithm is used to optimize the reliability of the motor hanger. The research results show that the combination of response surface method and structural reliability optimization method can simplify the solution process and improve the reliability of optimization results.
- motor hangers /
- response surface model /
- reliability optimization /
- multi-objective genetic algorithm

HTML全文

图 1 基于响应面法的多目标可靠性优化流程

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图 2 电机吊架结构几何模型

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图 3 电机吊架结构有限元模型

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图 4 极限函数均值样本趋势

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图 5 电机吊架的灵敏度

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图 6 响应面模型

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表 1 输入变量参数

序号	名称	函数分布	均值/mm	变异系数
1	X₁	正态分布	8.0	0.05
2	X₂	正态分布	10.0	0.05
3	X₃	正态分布	10.0	0.05
4	X₄	正态分布	12.0	0.05
5	X₅	正态分布	10.0	0.05
6	X₆	正态分布	10.0	0.05
7	X₇	正态分布	8.0	0.05
8	X₈	正态分布	8.0	0.05
9	X₉	正态分布	8.0	0.05
10	X₁₀	正态分布	10.0	0.05

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表 2 设计变量的初始值与边界值

设计变量	初始值/mm	边界值/mm
设计变量	初始值/mm	下限	上限
X₆	10	9	11
X₉	8	7	9
X₁₀	10	9	11

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表 3 中心组合试验设计及响应值

序号	X₆/mm	X₉/mm	X₁₀/mm	SEQV/MPa	USUM/mm
1	10	8	10	338.06	3.901
2	9	8	10	340.27	4.106
3	11	8	10	335.81	3.728
4	10	7	10	373.75	3.984
5	10	9	10	308.41	3.827
6	10	8	9	343.98	4.017
7	10	8	11	331.95	3.795
8	9.187	7.349 6	9.187	373.84	4.241
9	10.813	7.349 6	9.187	370.71	3.911
10	9.187	8.650 4	9.187	320.37	4.099
11	10.813	8.650 4	9.187	314.72	3.784
12	9.187	7.349 6	10.813	361.24	4.037
13	10.813	7.349 6	10.813	359.71	3.739
14	9.187	8.650 4	10.813	311.55	3.908
15	10.813	8.650 4	10.813	307.45	3.621

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表 4 确定性优化与可靠性优化对比

函数	确定性优化		可靠性优化
函数	均值	可靠度/%	均值	可靠度/%
SEQV	325.81	-	301.27	-
USUM	3.728	-	3.565 1	-
Z(X)	19.19	82.35	43.73	95

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表 5 初始设计与优化设计对比

指标	初始设计	优化设计	变化量/%
X₆/mm	10	10.65	6.5
X₉/mm	8	8.63	7.87
X₁₀/mm	10	9.18	-8.2
SEQV/MPa	338.06	301.27	-10.88
USUM/mm	3.901 2	3.565 1	-8.62

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