目前，航空发动机管路系统的卡箍布局优化设计大多数为确定性优化，没有考虑卡箍刚度和人工装配误差等不确定因素，这些不确定因素的波动性可能会导致管路系统的输出响应与预计值有较大偏差，从而引起系统故障。为了在改善航空发动机管路系统振动性能的同时保证管路系统具有较强的可靠性与稳健性，本文以Z型管路为研究对象，提出一种以避开激振频率和降低振动频率分散度为目标的卡箍布局稳健优化设计方法。该方法首先采用壳单元和弹簧单元分别对管体和卡箍进行有限元建模；然后对设计参数进行拉丁超立方抽样，通过有限元模型计算样本的固有频率，并构造频率响应的高精度神经网络代理模型；最后采用蒙特卡罗模拟和改进型非支配遗传算法，展开了卡箍支撑位置的稳健优化设计。结果表明：该方法能在保证管路系统避开激振频率的设计要求基础上，有效地提高其动力学特性的稳健性。
Abstract
At present, the clamp layout optimization design of aero-engine piping system is mostly deterministic optimization, without considering the uncertainties such as clamp stiffness and manual assembly error. The fluctuation of these uncertainties may cause the output response of piping system to have a large deviation from the expected value, thus causing system failure. In order to improve the vibration performance of aero-engine piping system and ensure the piping system has strong reliability and robustness, a robust optimization design method for clamp layout is proposed in this paper, taking Z-type piping as the research object, which aims to avoid the excitation frequency and reduce the dispersion of vibration frequency. Firstly, shell element and spring element are used to model the tube body and clamp respectively. Then, the Latin hypercube sampling of the design parameters is carried out, the natural frequency of the samples is calculated by finite element model, and the high precision neural network proxy model of frequency response is constructed. Finally, Monte Carlo simulation and improved non-dominated genetic algorithm were used to carry out robust optimization design of clamp support position. The results show that the proposed method can effectively improve the robustness of dynamic characteristics on the basis of ensuring that the piping system avoids the design requirement of excitation frequency.
关键词
Z型管路 /
有限元建模 /
神经网络 /
遗传算法 /
稳健设计
{{custom_keyword}} /
Key words
Z-type pipeline /
Finite element modeling /
Neural network /
Genetic algorithm /
Robust design
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 于利磊, 唐文勇, 张圣坤, 等. 一种工程结构的鲁棒优化设计方法[J]. 上海交通大学学报, 2003, 37(8): 1189-1192.
YU Lilei, TANG Wenyong, ZHANG Shengkun, et al. Robust optimization design method for engineering structures [J]. Journal of Shanghai Jiaotong University, 2003, 37(8): 1189-1192.
[2] Wunsch D, Hirsch C, Nigro R, et al. Quantification of combined operational and geometrical uncertainties in turbo-machinery design[C]//Turbo Expo: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2015, 56659: V02CT45A018.
[3] 李小刚, 程锦, 刘振宇, 等. 基于双层更新 Kriging 模型的机械结构动态特性稳健优化设计[J]. 机械工程学报, 2014, 50(3): 165-173.
LI Xiaogang, CHENG Jin, LIU Zhenyu, et al. Robust optimization for dynamic characteristics of mechanical structures based on double renewal kriging model [J]. Journal of Mechanical Engineering, 2014, 50(3): 165-173.
[4] Yıldız A R, Erdaş M U. A new Hybrid Taguchi-salp swarm optimization algorithm for the robust design of real-world engineering problems[J]. Materials Testing, 2021, 63(2): 157-162.
[5] 赵欢, 高正红, 夏露. 高速自然层流翼型高效气动稳健优化设计方法[J]. 航空学报, 2022, 43(01): 271-288.
ZHAO Huan, GAO Zhenghong, XIA Lu. Efficient robust aerodynamic design optimization method for high-speed NLF airfoil. Acta Aeronautica et Astronautica Sinica, 2022, 43(01): 271-288.
[6] 聂祚兴, 于德介, 周建文, 等. 基于6σ的车身噪声传递函数稳健优化设计[J]. 振动与冲击, 2014, 33(14): 155-159.
NIE Zuoxin, YU Dejie, ZHOU Jianwen, et al. Robust optimization design for car bodies’ noise transfer functions based on six sigma[J]. Journal of Vibration and Shock, 2014, 33(14): 155-159.
[7] 张政, 周长聪, 戴志豪, 等. 基于重要性测度降维的液压管路稳健优化设计[J]. 航空学报, 2018, 39(08): 281-289.
ZHANG Zheng, ZHOU Changcong, DAI Zhihao, et al. Robust optimization of hydraulic piping system based on importance measure dimension-reduction. Acta Aeronautica et Astronautica Sinica, 2018, 39(08): 281-289.
[8] Kwong A H M, Edge K A. A method to reduce noise in hydraulic systems by optimizing pipe clamp locations[J]. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 1998, 212(4): 267-280.
[9] 李鑫, 王少萍. 基于卡箍优化布局的飞机液压管路减振分析[J]. 振动与冲击, 2013, 32(1): 14-20.
LI Xin, WANG Shaoping. Vibration control analysis for hydraulic pipelines in an aircraft based on optimized clamp layout. Journal of Vibration and Shock, 2013, 32(1): 14-20.
[10] 张禹, 公健, 唐滋阳, 等. 基于改进多目标人工蜂群算法的航空发动机管路智能布局方法[J]. 机械工程学报, 2022, 58(4): 277-284.
ZHANG Yu, GONG Jian, TANG Ziyang, et al. Method for intelligent aeroengine pipeline layout based on improved multi-objective artificial bee colony algorithm. Journal of Mechanical Engineering, 2022, 58(4): 277-284.
[11] Herrmann J, Haag T, Gaul L. Experimental and numerical investigation of the dynamics in spatial fluid-filled piping systems[J]. Journal of the Acoustical Society of America, 2008, 123(5): 5557－5562.
[12] 高志辉, 王东海, 孙伟, 等. L型管路系统动力学有限元建模及基于遗传算法的卡箍支撑位置优化[J].振动与冲击, 2022, 41(16): 149-157.
GAO Zhihui, WANG Donghai, SUN Wei, et al. Establishment of a dynamic finite element model of an L-type pipeline system and optimization of hoop supporting position based on the genetic algorithm. Journal of Vibration and Shock. 2022, 41(16): 149-157.
[13] Tang Z, Lu Z, Li D, et al. Optimal design of the positions of the hoops for a hydraulic pipelines system[J]. Nuclear engineering and design, 2011, 241(12): 4840-4855.
[14] Gao P, Zhai J, Yan Y, et al. A model reduction approach for the vibration analysis of hydraulic pipeline system in aircraft[J]. Aerospace Science and Technology, 2016, 49: 144-153.
[15] Gan Y, Duan Q, Gong W, et al. A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model[J]. Environmental modelling & software, 2014, 51: 269-285.
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
PDF(2990 KB)
