Electric potential structures of auroral acceleration region border from multi-spacecraft Cluster data

This paper studies an auroral event using data from three spacecraft of the Cluster mission, one inside and two at the poleward edge of the bottom of the Auroral Acceleration Region (AAR). The study reveals the three-dimensional profile of the region’s poleward boundary, showing spatial segmentation of the electric potential structures and their decay in time. It also depicts localized magnetic field variations and field-aligned currents that appear to have remained stable for at least 80?s. Such observations became possible due to the fortuitous motion of the three spacecraft nearly parallel to each other and tangential to the AAR edge, so that the differences and variations can be seen when the spacecraft enter and exit the segmentations, hence revealing their position with respect to the AAR.     

Experimental study on plasma jet deflection and energy extraction with MHD control

This paper presents an integrated research scheme for vector deflection and energy extraction in a gas plasma jet under Magneto-Hydrodynamic (MHD) control. A MHD-controlled thrust-vector test rig was used to conduct the experimental research. A gas plasma was obtained by injecting ionization seeds of Cs₂CO₃ into the combustion chamber via artificially forced ionization. The effects of the gas temperature and ionization seed mass fraction on the plasma jet deflection and energy extraction were experimentally verified under an applied magnetic field. The experimental results were analyzed theoretically. The results showed that the deflection amplitude of the gas plasma jet and the extracted voltage signal intensity increased with increasing gas temperature and the ionization seed mass fraction. The extracted dynamic voltage signals proved that the ionization seeds of Cs₂CO₃ induced gas ionization at 1173 K. The experiment verified that it is feasible to simultaneously achieve jet deflection and extract energy under the action of an external magnetic field.     

Aircraft nonlinear stability analysis and multidimensional stability region estimation under icing conditions

Icing is one of the crucial factors that could pose great threat to flight safety,and thus research on stability and stability region of aircraft safety under icing conditions is significant for control and flight.Nonlinear dynamical equations and models of aerodynamic coefficients of an air craft are set up in this paper to study the stability and stability region of the aircraft under an icing condition.Firstly,the equilibrium points of the iced aircraft system are calculated and analyzed based on the theory of differential equation stability.Secondly,according to the correlation theory about equilibrium points and the stability region,this paper estimates the multidimensional stability region of the aircraft,based on which the stability regions before and after icing are compared.Finally,the results are confirmed by the time history analysis.The results can give a reference for stability analysis and envelope protection of the nonlinear system of an iced aircraft.     

嫦娥四号动力下降段图像可视化传输方案

针对嫦娥四号降落相机在动力下降段的图像可视化传输需求和深空通信下行数传信道带宽受限的矛盾,文章提出了一种动力下降段速率自适应的可视化图像传输方案,对如何保证降落相机图像下传的实时性、完整性、速率自适应性等关键问题进行了讨论,并对方案中涉及的抽帧回放算法、帧格式识别方法、合路调度算法等关键技术进行了详细说明。同时,文中给出了该方案在嫦娥四号在轨的验证情况,结果表明,在数传通信速率受限的情况下该方案实现了降落相机图像的存储管理和可视化下传,具有实时性高、速率自适应、图像下传完整等特点,可以为其他航天器数据管理系统设计提供参考。     

基于表观细粒度辨别网络的近海船舶目标检测方法

近海船舶目标检测是一项非常具有挑战性的任务,受到学者专家广泛关注。基于卷积神经网络（CNN）和注意力机制的检测器在近海船舶目标检测方面的应用取得了显著成就。然而,船舶目标检测存在着表观相似和背景干扰导致检测过程中出现误检的问题。为此,本文提出了一种用于Faster RCNN（更快的基于区域的卷积神经网络）的表观细粒度辨别的检测头模块。该模块包括类别细粒度分支和高效全维动态卷积定位分支。其中类别细粒度分支通过全局特征建模和灵活的感知范围来挖掘和利用类别细粒度辨别特征,高效全维动态卷积定位分支通过高效灵活的感知船舶边界信息来区分目标与背景,从而减少误检漏检问题。通过在近海船舶公开数据集Seaships7000 上进行实验验证,本文算法减少了误检漏检,提升了检测器性能。     

飞机框肋类零件外形样板三维快速设计原理及算法

作为近年来飞机型号研制中常用的内外形控制与协调方式,飞机样板因其使用便捷、成本低廉、技术成熟等优势,在当前飞机研制中仍具有不可替代性。在当前智能化技术快速发展的数字化环境下,依赖二维图纸的样板设计技术已明显成为制约飞机研制效率和周期的重要因素,研究和开发以框肋类零件三维几何模型为基础的样板三维设计技术已成为当前航空产业的迫切需要。针对上述问题,对框肋类零件样板的一大分支--外形样板的三维快速设计原理及算法展开研究,提出钣金零件几何属性提取及外形样板三维快速设计算法,主要内容为:提出框肋类零件基础结构特征定义及提取方法,基于提取结果构建零件弯边特征并计算样板设计所需几何属性,提出外形样板轮廓计算及补加添加算法,最终实现零件外形样板三维模型生成。经由实例测试,验证此算法的可行性与有效性。     

利用神经网络规则提取方法获取转静碰摩故障诊断知识

 获取易于理解的航空发动机转静碰摩故障诊断知识规则对于深刻认识碰摩故障机理、有效诊断碰摩故障具有重要意义。鉴于此,研究了一种新的基于功能性观点的神经网络（NN）规则提取方法,介绍了连续属性离散、训练样本产生、神经网络训练、示例样本产生及规则提取等关键算法,并用Iris数据对方法进行了验证。最后,通过航空发动机转子实验器获取碰摩故障样本,利用神经网络规则提取方法从故障样本中提取了碰摩故障诊断知识规则,并对其进行了验证分析,验证结果充分表明了该方法的正确有效性。     

一种划定反舰导弹飞行航区的方法研究

考虑到反舰导弹试验与训练的安全性,引入反舰导弹飞行航区的定义.探讨了4个影响飞行航区划定因素:舰面干扰、风干扰、陀螺漂移干扰、导弹故障干扰,构建了反舰导弹干扰作用下的全弹道模型.进而以设定的导弹参数为例,划定飞行航区,通过与实际靶试对照,验证了该方案的合理性与优越性.     

基于小波神经网络的齿轮系统故障诊断

通过对齿轮系统在不同的运转状态下不同的故障类型进行试验测试分析,获取了有关的测试信号,对振动特征信号进行了小波阈值去噪,采用离散小波变换(DWT)对去噪后的信号进行8层分解处理,对各层的小波系数进行了小波重构,得到8层细节信号和1层近似信号,并计算了各层信号的能量,得到了信号的能量分布特征.在此基础上把各层信号特征作为神经网络的输入,进行了网络的研究、分析处理和故障分类,并对小波神经网络方法与单独采用神经网络方法的故障诊断结果进行了比较评价.研究表明,去噪处理后的效果比没有去噪的信号特征更加明显,而采用小波神经网络诊断方法,对于齿轮无故障、齿根裂纹故障、分度圆裂纹故障和齿面磨损故障能够进行很好地区分与诊断,其诊断成功率均在95%以上,可对实际工程工作的齿轮系统进行故障诊断.      

高超声速飞行器跨流域气动力／热预测技术研究

分析了跨流域流动特点、工程背景需求、国内外研究现状,针对高超声速飞行器跨流域气动力／热预测存在的主要问题,从粘性干扰参数与克努森数搭接的跨流域模拟准则、微量天平结构优化及测力技术、红外大面积中低量值热流测量技术、流场显示与测量技术和 N-S／DSMC 自适应紧耦合数值模拟方法等方面,总结了近年来取得的研究进展,并讨论了下一步研究方向。