基于代理模型和敏感度分析的直升机主减速器减振优化

许华超; 朱豪杰; 韩振华; 王勇; 秦大同

doi:10.13224/j.cnki.jasp.20220884

基于代理模型和敏感度分析的直升机主减速器减振优化

doi: 10.13224/j.cnki.jasp.20220884

许华超^{1, 2},
朱豪杰³,
韩振华^4,*, ,,
王勇^{1, 2},
秦大同²

1.
重庆电子科技职业大学智能制造与汽车学院，重庆 401331
2.
重庆大学机械传动国家重点实验室，重庆 400044
3.
天津航天长征技术装备有限公司，天津 300462
4.
江苏理工学院机械工程学院，江苏常州 213001

基金项目: 国家自然科学基金（52005229）；重庆市教委科学技术研究项目（KJQN202203121，KJZD-K202203105）；重庆电子工程职业学院校级科研项目（22XJZXYB14）；江苏省基础研究计划（BK20201055）

详细信息

作者简介:
许华超（1990-），男，讲师，博士，主要从事直升机主减速器动力学设计与分析方面的研究

通讯作者:
韩振华（1986-），男，讲师，博士，主要从事齿轮传动设计理论与方法方面的研究。E-mail：han_jsut@jsut.edu.cn

中图分类号: V275；TH113
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出版历程
- 收稿日期: 2022-11-19
- 网络出版日期: 2024-05-07

Vibration reduction optimization for helicopter’s main gearbox based on surrogate model and sensitivity analysis

XU Huachao^{1, 2},
ZHU Haojie³,
HAN Zhenhua^{4,*
, ,},
WANG Yong^{1, 2},
QIN Datong²

1.
College of Intelligent Manufacturing and Automotive，Chongqing Polytechnic University of Electronic Technology，Chongqing 401331，China
2.
State Key Laboratory of Mechanical Transmission，Chongqing University，Chongqing 400044，China
3.
Tianjin Aerospace Long March Technical and Equipment Company，Limited，Tianjin 300462，China
4.
College of Mechanical Engineering，Jiangsu University of Technology，Changzhou Jiangsu 213001，China

摘要

摘要:
针对直升机主减速器减振优化存在计算量大、参数多等问题，提出了基于代理模型和全局敏感度分析的直升机主减速器减振优化方法。定义振动性能的评价指标，运用最优拉丁超立方抽样法均匀抽取样本数据，并依次带入直升机主减速器动力学模型求解评价指标样本；采用代理模型构建并替代计算耗时的主减速器动力学模型，以提高优化效率；随后开展参数敏感度分析，确定优化变量，并采用遗传算法在优化参数的取值范围内搜索出最优参数值。结果表明：代理模型能有效替代直升机主减速器动力学模型，啮合刚度是影响系统振动的重要参数，优化后主减速器各测点的振动加速度有效值最大与最小降幅分别为18.01%和4.28%。
- 直升机 /
- 主减速器 /
- 减振 /
- 敏感度分析 /
- 代理模型
Abstract:
In view of the problems of large amount of calculation and many parameters in the vibration reduction optimization for helicopter’s main gearbox, an optimal design method for vibration reduction of helicopter’s main gearbox based on surrogate model and global sensitivity analysis was proposed. The evaluation index of the vibration performance was defined. The optimal Latin hypercube sampling method was used to evenly extract the sample data, which were brought into the dynamic model of the helicopter’s main gearbox to obtain the evaluation index samples. The surrogate model was used to construct and replace the time-consuming dynamic model of main gearbox to improve the optimization efficiency. Subsequently, parameter sensitivity analysis was conducted to determine the optimization variables, and genetic algorithms were used to search for the optimal parameter values within the range of optimization parameters. The results showed that the surrogate model can effectively replace the dynamics model of the helicopter’s main gearbox. The meshing stiffness served as an important parameter affecting the system vibration. After optimization, the maximum and minimum reductions in the effective value of vibration acceleration at each measuring point of the main reducer were 18.01% and 4.28%, respectively.
- helicopter /
- main gearbox /
- vibration reduction /
- sensitivity analysis /
- surrogate model

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图 1 行星齿轮系统动力学模型

Figure 1. Dynamic model of planetary gear system

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图 2 斜齿轮动力学模型

Figure 2. Helical gear dynamic model

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图 3 螺旋锥齿轮啮合模型

Figure 3. Spiral bevel gear mesh model

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图 4 螺旋锥齿轮受力分析

Figure 4. Force analysis of spiral bevel gear

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图 5 传动轴有限元模型

Figure 5. Finite element model of transmission shaft

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图 6 考虑轴和机匣结构柔性的直升机主减速器动力学模型

Figure 6. Dynamic model of helicopter main gearbox considering flexibility of shaft and housing

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图 7 代理模型预测精度对比

Figure 7. Prediction accuracy comparison of surrogate models

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图 8 系统参数敏感度分析

Figure 8. Sensitivity analysis of system parameters

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图 9 不同负载下优化前后各测点的振动

Figure 9. Vibration of each measuring point before and after optimization under different loads

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表 1 模型参数的初值及取值范围

Table 1. Initial value and value range of model parameters 10⁸ （N/m）

模型参数	初值	取值范围
高速级平均啮合刚度x₁	5.7	[5.55, 5.87]
中间级平均啮合刚度x₂	4.8	[4.65, 4.94]
低速级平均啮合刚度x₃	3.7	[3.58, 3.81]
行星级平均啮合刚度x₄	9.5	[9.21, 9.78]
行星轮轴承支撑刚度x₅	0.034	[0.0329, 0.0350]
齿圈与机匣间刚度x₆	21	[19.4, 20.6]
轴承1, 2的支撑刚度x₇	0.15	[0.146, 0.155]
轴承3, 4的径向刚度x₈	5.1	[4.94, 5.25]
轴承3, 4的轴向刚度x₉	1.7	[1.64, 1.75]
轴承5, 6的径向刚度x₁₀	4.1	[3.97, 4.22]
轴承5, 6的轴向刚度x₁₁	3.4	[3.29, 3.50]
轴承7, 8的径向刚度x₁₂	5.5	[5.33, 5.66]
轴承7, 8的轴向刚度x₁₃	6.2	[6.01, 6.38]
轴承9, 10的径向刚度x₁₄	4.2	[4.07, 4.32]
轴承9, 10的轴向刚度x₁₅	2.0	[1.94, 2.06]

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表 2 优化前后的模型参数

Table 2. Model parameters before and after optimization

参数	优化前/ 10⁸ （N/m）	优化后/ 10⁸ （N/m）	ζ/%
x₁	5.7	6.5	14.0
x₃	3.7	3.0	18.9
x₄	9.5	7.8	17.3
x₈	5.1	6.2	22.5
x₁₀	4.1	4.8	16.8
x₁₂	5.5	4.7	13.5

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表 3 额定工况下系统优化前后各测点的振动响应

Table 3. Vibration response of each measuring point before and after system optimization under rated condition

测点	振动响应
测点	优化前/（m/s²）	优化后/（m/s²）	改善率/%
1	260.17	217.30	16.36
2	96.19	91.83	5.31
3	242.77	212.70	12.28
4	189.65	169.78	10.07
5	133.53	122.80	7.92

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