基于不确定性的飞行器分离可靠性建模与分析方法

为实现飞行器分离任务可靠性的定量分析和高效精确评估，研究了高超声速飞行器分离任务过程中各种不确定性因素对分离可靠性的影响，提出一种基于不确定性的飞行器分离可靠性建模与分析方法。面向高超声速飞行器分离任务需求，建立分离动力学仿真模型，综合考虑分离过程不确定性因素的影响，利用灵敏度分析方法识别主要不确定性因素，构建分离可靠性模型。针对此模型，提出一种改进主动学习Kriging(IAK)的分离可靠性分析方法，通过新的采样策略选取失效概率更大的采样点作为新增训练点，进行高效可靠性分析。实例结果表明，该方法能够准确描述不确定性因素对分离过程的影响，提升分离可靠性定量分析的精度和效率，为飞行器分离方案的精细化设计提供支撑。     

Bayesian network-based extraction of lunar impact craters from optical images and DEM data

Impact craters are among the most noticeable geomorphological features on the planetary surface and yield significant information about terrain evolution and the history of the solar system. Thus, the recognition of impact craters is an important branch of modern planetary studies. Aiming at addressing problems associated with the insufficient and inaccurate detection of lunar impact craters, a decision fusion method within the Bayesian network (BN) framework is developed in this paper to handle multi-source information from both optical images and associated digital elevation model (DEM) data. First, we implement the edge-based method for efficiently searching crater candidates which are the image patches that can potentially contain impact craters. Secondly, the multi-source representations of an impact crater derived from both optical images and DEM data are proposed and constructed to quantitatively describe the two-dimensional (2D) and three-dimensional (3D) morphology, consisting of Histogram of Oriented Gradient (HOG), Histogram of Multi-scale Slope (HMS) and Histogram of Multi-scale Aspect (HMA). Finally, a BN-based framework integrates the multi-source representations of impact craters, which can provide reductant and complementary information, for distinguishing craters from non-craters. To evaluate the effectiveness and robustness of the proposed method, experiments were conducted on three lunar scenes using both orthoimages from the Lunar Reconnaissance Orbiter (LRO) and DEM data acquired by the Lunar Orbiter Laser Altimeter (LOLA). Experimental results demonstrate that integrating optical images with DEM data significantly decreases the number of false positives compared with using optical images alone, with F₁-score of 84.8% on average. Moreover, compared with other existing fusion methods, our proposed method was quite advantageous especially for the detection of small-scale craters with diameters less than 1000 m.     

月球表层采样样品智能确认方法

表层采样是月球采样探测的重要方式，样品智能确认有助于提升工作效率与复杂问题处理能力。结合月球表层采样铲挖工作过程，分析了铲挖过程中臂载相机图像的特点，模仿有人参与识别过程，提出了层次解耦的月球样品智能识别流程，利用深度学习方法构建了一类深度卷积识别网络，完整地描述了图像、特征、标记在网络中的正反传递关系，并在月球表层采样地面试验中进行了验证，结果表明该方法对不同光照、不同背景、不同过程、不同形态的样品，具有较好的泛化识别能力，误识别率优于8.1%，平均单幅识别时间约0.7 s。     

基于核主成分分析的空域复杂度无监督评估

空域复杂度评估作为衡量空域运行态势、管制员工作压力的关键手段，是运行调控的基础。由于影响因素众多，不同因素间耦合关联复杂，且标定样本很难获取，空域复杂度的准确评估被公认为航空领域的一个挑战性问题。提出了一种空域复杂度的无监督评估方法。首先通过核主成分分析挖掘原始样本各维度的非线性耦合关系，准确提取能够最大化复杂度评估信息量的主成分，进一步设计了可按需定制的主成分聚类方法，实现了无监督条件下空域复杂度的准确评估，为空域划分、流量管理提供了有效的技术支撑。     

Stall flutter prediction based on multi-layer GRU neural network

The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model (ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit (GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation (LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.     

基于集成学习模型的飞行学员认知负荷研究

在飞行过程中,飞行员需要在短时间内接收大量信息,并做出正确的判断与决策,而过高的认知负荷会影响其感知、判断、决策等认知过程,进而影响飞行安全。首先通过飞行模拟实验获取飞行学员在执行不同飞行任务时的生理数据;然后通过时域、频域分析等方法提取呼吸和心电信号的特征,并通过统计学方法筛选出能够反映认知负荷水平的指标;最后结合支持向量机、K 最邻近、人工神经网络等方法建立集成学习模型,对飞行学员的认知负荷进行评估,并与单一算法进行对比。结果表明：本文建立的集成学习模型具有较高的准确率,能够更好地反映飞行学员认知负荷水平。     

Collaborative image compression and classification with multi-task learning for visual Internet of Things

Widespread deployment of the Internet of Things(Io T) has changed the way that network services are developed, deployed, and operated. Most onboard advanced Io T devices are equipped with visual sensors that form the so-called visual Io T. Typically, the sender would compress images, and then through the communication network, the receiver would decode images, and then analyze the images for applications. However, image compression and semantic inference are generally conducted separately, and t...     

圆柱管多分支联接三维分块贴体网格的耦合生成

利用分块耦合技术生成了两圆柱管成任意角度,管径不相等的三分支联接的三维贴体网格,所介绍的网格生成方法在分块生成网格时能保证穿过分界面上的网格线是光滑连续的。此外,用方法生成网格时间通过边界上网格的疏密或者稳定边界上网格线之间的夹角来控制内部区域的网格疏密。     

语言学习策略——部分高校理工科学生英语学习运用策略调查

语言学习策略（Ｌａｎｇｕａｇｅｌｅａｒｎｉｎｇｓｔｒａｔｅｇｉｅｓ）是学习者用于提高学习效率所采用的方法和步骤。作者调查了中国部分高校理工科大学生在英语学习中运用语言学习策略的能力。调查采用了Ｏｘｆｏｒｄ的一套自我测试调查表。根据我国学生的实际情况对调查表中某些项目做了适当的修改。调查涉及两个高校两个年级的３００名学生,并采用科学的方法进行统计,结果表明语言学习策略与英语学习有密切联系;语言学习策略对中国学生学习外语十分重要。     

日地平动点卫星两脉冲转移轨道设计

研究基于最小二乘微分修正方法的平动点卫星两脉冲转移轨道设计,推导了考虑高度和航迹角约束的微分修正公式,讨论了该方法的收敛性.以日地L₁点附近的Halo轨道为目标轨道,在圆型限制性三体问题模型下设计了其转移轨道,系统地研究了HOI(Halo Orbit Insertion)点和Halo轨道幅值对转移轨道的影响,给出了HOI点的选择策略,并讨论了应急情况下快速转移轨道设计.数值仿真验证了方法的有效性,选择Halo轨道靠近地球侧的点作HOI点可以获得飞行时间适中的转移轨道.