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基于差分进化算法的飞机油量传感器布局优化方法

郑帅1,王子涵1,赵浩然1,杨朋涛2,洪军3   

  1. 1. 西安交通大学软件学院
    2. 西安沃祥航空科技有限公司
    3. 西安交通大学
  • 收稿日期:2021-05-17 修回日期:2021-09-29 出版日期:2021-10-09 发布日期:2021-10-09
  • 通讯作者: 郑帅
  • 基金资助:
    国家自然科学基金青年项目

Layout optimization method of aircraft fuel sensor based on differential evolution algorithm

  • Received:2021-05-17 Revised:2021-09-29 Online:2021-10-09 Published:2021-10-09

摘要: 针对飞机油量测量传感器布局问题,综合考虑底部不可测量油量、顶部不可测量油量、姿态误差三个指标,设计并实现了一种基于差分进化算法的飞机油量传感器多目标布局优化方法。通过建立初始传感器安装线集合将连续优化空间转换为离散优化空间,解决了安装约束问题。通过分析优化目标建立了考虑倾斜传感器的布局指标评估方法。将离散型变异算子引入标准差分进化算法,并使用NSGA-Ⅱ中的快速非支配排序、拥挤度计算策略解决传感器布局中的多目标优化问题。通过OpenMP并行计算技术优化求解速度。最后,进行了优化实验,结果表明,该方法实现了飞机油量测量传感器布局的多目标优化,且在求解质量和优化速度方面明显优于对比方法。

关键词: 飞机燃油测量, 油量传感器布局, 多目标优化, 差分进化算法, 快速非支配排序

Abstract: Aiming at the layout problem of aircraft fuel measurement sensor, a multi-objective layout optimization method of aircraft fuel measurement sensor based on differential evolution algorithm was designed and implemented considering three indexes of unmeasurable fuel at the bottom, unmeasurable fuel at the top and attitude error. The installation constraint problem is solved by establishing an initial set of sensor installation lines to transform the continuous optimization space into a discrete optimization space. By analyzing the optimization objective, an evaluation method of the sensor layout index considering the tilt installation is established. The discrete mutation operator is introduced into the standard differential evolution algorithm, and the fast non-dominated sorting and congestion calculation strategies in NSGA-Ⅱ are used to solve the multi-objective optimization problem in the sensor layout. The solution speed is optimized by using OpenMP parallel computing technology. Finally, the optimization experiment is carried out, and the results show that the proposed method realizes the multi-objective optimization of the layout of the aircraft fuel measurement sensor, and is obviously superior to the comparison algorithm in terms of solving quality and optimization speed.

Key words: aircraft fuel measurement, fuel sensor layout, multi-objective optimization, differential evolution algorithm, fast non-dominated sorting

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