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飞机机翼数字孪生模型验证试验方案设计

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近年来数字孪生逐渐成为军用仿真领域的研究重点.为确保数字孪生模型的可信度,验证试验至关重要.现有某型飞机机翼的重量受到多个因子的影响,根据其数字孪生模型,仿真生成部分试验数据,采用基于高斯过程的非参数回归和基于粒子群算法的参数回归2种方法构建这些因子与机翼重量的影响模型.给出一种基于贝叶斯的修正幂先验的验证试验样本量确定方法,提出基于粒子群算法的试验设计方法,解决了试验设计容易陷入局部最优解的问题.最后,结合案例进行试验,结果验证了上述方法的有效性.
Aircraft Wing Digital Twin Model Validation Test Program Design
Digital twins have gradually become a research focus in military simulation in recent years.In order to ensure the credibility of the digital twin model,validation tests are crucial.The weight of the wing of a certain type of existing aircraft is affected by several factors,and according to its digital twin model,some test data are generated by simulation,and the two methods of non-parametric regression based on Gaussian process and parametric regression based on particle swarm algorithm are used to construct a model of the influence of these factors on the weight of the wing.A method of determining the sample size of validation test based on the Bayesian-based modified power prior is put forward.A test design method based on the particle swarm algorithm is proposed,which prevents the test design from falling into the local optimal solution.Finally,experiments are carried out in combination with cases,and the results verify the effectiveness of the above methods.

digital twinmodel credibilityexperimental designparticle swarm algorithmsample size calculation

张城铭、陈婧、刘瑞鹏、李天逸、余晨阳、朱正秋

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国防科技大学 系统工程学院,湖南 长沙 410073

中国人民解放军空军95209部队,湖南 长沙 410000

数字孪生 模型可信度 试验设计 粒子群算法 样本量计算

2024

系统仿真技术
同济大学

系统仿真技术

CSTPCD
影响因子:0.271
ISSN:1673-1964
年,卷(期):2024.20(3)