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论文:2019,Vol:37,Issue(2):218-224 |
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引用本文： |
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薛小锋, 王远卓, 路成. 基于改进Kriging模型的舰载机着舰下沉速度影响性分析研究[J]. 西北工业大学学报 |
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XUE Xiaofeng, WANG Yuanzhuo, LU Cheng. Sinking Velocity Compact-Analysis of Carrier-Based Aircraft Based on Improved Kriging Model[J]. Northwestern polytechnical university |
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| 基于改进Kriging模型的舰载机着舰下沉速度影响性分析研究 |
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| 薛小锋1, 王远卓2, 路成1 |
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1. 西北工业大学 航空学院, 陕西 西安 710072;
2. 西北工业大学 航天学院, 陕西 西安 710072 |
| 摘要: |
| 着舰下沉速度是舰载机起落架及其连接结构载荷设计的重要输入，直接影响到起落架和机体结构重量。为了探索舰载机使用环境下各参数对下沉速度的影响，基于F/A-18A飞机的实测着舰数据，采用多元统计学中偏相关分析方法分析了15个着舰参数与下沉速度的相关程度，结果表明飞机瞬时下滑角、甲板俯仰角与下沉速度呈高度相关，进场速度、舰上接合速度与下沉速度呈中度相关。以上述4个着舰参数作为自变量，将遗传算法用于相关函数待定系数的优化求解，并建立了F/A-18A飞机下沉速度改进的Kriging插值代理模型。所建模型给出的下沉速度预测结果的复相关系数为0.981、平均相对误差为1.813%及最大相对误差为6.771%，与经验公式及普通Kriging模型对比，精度指标均为最好。所提改进Kriging模型及得到的分析结果可为类似型号舰载机下沉速度研究及着舰姿态控制提供依据。 |
| 关键词:
舰载机
下沉速度
相关分析
遗传算法
Kriging模型
影响性分析
多元统计
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| Sinking Velocity Compact-Analysis of Carrier-Based Aircraft Based on Improved Kriging Model |
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| XUE Xiaofeng1, WANG Yuanzhuo2, LU Cheng1 |
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1. School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China;
2. School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China |
| Abstract: |
| The sinking velocity of carrier-based aircraft is an important input for landing gear design, and has a great influence on the weight of the landing gear and airframe structure. Aiming at exploring the effect of the various related landing parameters on the sinking velocity for carrier-based aircraft at the actual service environment, and based on F/A-18A measured landing data, the correlation degree between 15 landing parameters and sinking velocity is analyzed by partial correlation analysis method in multivariate statistics. The results show that the aircraft instantaneous gliding angle and deck pitch angle are highly correlated with the sinking velocity, the approach velocity and the engaging velocity are moderately correlated with the sinking velocity. The above four parameters are used as the independent variables, an improved Kriging surrogate model for the sinking velocity of F/A-18A aircraft is established, and Genetic algorithm is used to optimize the undetermined coefficients of correlation functions. The complex correlation coefficient of the sinking velocity predicted by the proposed model is 0.981, the average relative error is 1.813% and the maximum relative error is 6.771%. And comparing the empirical formula with the ordinary Kriging model, the precision index is the best. The proposed model provides the best prediction results. The improved Kriging surrogate model and the results obtained in this paper can provide a basis for studying the sinking velocity and controlling landing attitude for similar models carrier-based aircraft. |
| Key words:
carrier-based aircraft
sinking velocity
correlation analysis
genetic algorithm
Kriging model
compaction-analysis
multivariate statistics
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| 收稿日期: 2018-05-02
修回日期:
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| DOI: 10.1051/jnwpu/20193720218 |
| 基金项目: 国家自然科学基金（51875465）资助 |
| 通讯作者:
Email： |
| 作者简介: 薛小锋(1982-),西北工业大学讲师、博士,主要从事飞行器设计、可靠性工程研究。
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| 作者相关文章 |
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| 薛小锋 在本刊中的所有文章 |
| 王远卓 在本刊中的所有文章 |
| 路成 在本刊中的所有文章 |
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