基于离散优化的飞行试验点优化设计方法

刘思余; 梁言; 马明明

doi:10.7638/kqdlxxb-2021.0347

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基于离散优化的飞行试验点优化设计方法

研究论文 | 更新时间：2026-05-28

- 基于离散优化的飞行试验点优化设计方法
- Optimal flight test design method based on discrete optimization
- 空气动力学学报 2023年41卷第1期页码：86-92
- 作者机构：
  
  中国飞行试验研究院发动机所,西安,710089
- 作者简介：
  
  刘思余*（1993-），男，工程师，硕士，主要从事航空发动机工作特性研究. E-mail：liusy_avic@163.com
- 基金信息：
- DOI：10.7638/kqdlxxb-2021.0347
  中图分类号： V217.1
- 纸质出版：2023
- 稿件说明：
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刘思余, 梁言, 马明明. 基于离散优化的飞行试验点优化设计方法[J]. 空气动力学学报, 2023, 41(1): 86−92.

LIU Siyu, LIANG Yan, MA Mingming. Optimal flight test design method based on discrete optimization[J]. 2023, 41(1): 86-92.
刘思余, 梁言, 马明明. 基于离散优化的飞行试验点优化设计方法[J]. 空气动力学学报, 2023, 41(1): 86−92. DOI： 10.7638/kqdlxxb-2021.0347

LIU Siyu, LIANG Yan, MA Mingming. Optimal flight test design method based on discrete optimization[J]. 2023, 41(1): 86-92. DOI： 10.7638/kqdlxxb-2021.0347.

摘要

为了更好地规划飞行试验点以提高试验效率，本文进行了基于离散优化的飞行试验点优化设计。通过显著性检验量化不同自变量对推力模型的影响大小，并依次剔除影响较小的自变量，得到了航空发动机推力模型。首先采用D-最优准则评估试验点组合集的优劣，然后利用自适应遗传算法进行试验点离散优化，并以试验点组合的方式取代遗传算法中的二进制编码过程，在试验限制条件下计算试验点最优组合集。以航空发动机性能试飞为案例进行应用，结果表明：试验点优化设计不仅与试验点的分布有关，也与试验点的数量有关。初始试验点最优组合集的试验点数量为12，得到的推力模型最大误差达到2.45%；最终试验点最优组合集的试验点数量为23，得到的推力模型最大误差不超过0.81%。通过研究表明，本文采用的试验点优化设计方法能够有效得到试验点最优组合集，提高模型精度，满足工程使用需求。

Abstract

To improve the flight test efficiency by designing test points

this paper develops the optimal flight test design method based on discrete optimization. This study establishes an aero-engine performance thrust model by quantizing the effects of different variables on the thrust model based on the significance test

and removing those insignificant variables. The D-optimal is first used to evaluate the quality of the test point combination. Then the test point discrete optimization is performed with an adaptive genetic algorithm whose encoding process is replaced by the test point combination

such that the optimal test point combination is obtained under the test constraint. The discrete optimization based test design method is applied for the aero-engine performance flight test

and the results show that: The optimization is not only related to the test point distribution

but also related to the number of test points. When the initial number of the optimal test point combination is 12

the max error of the thrust model is 2.45%; when the final number of the optimal test point combination is 23

the max error of the thrust model is less than 0.81%. The present method can obtain the optimal test point combination effectively

improve the accuracy of the thrust model

and meet the requirements of engineering applications.

关键词

Keywords

references

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