A multi-aircraft conflict detection and resolution method for 4-dimensional trajectory-based operation

Conflict Detection and Resolution(CDR) is the key to ensure aviation safety based on Trajectory Prediction(TP). Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional(4D) Trajectory-Based Operation(4DTBO), which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CDR from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CDR scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism(STP) for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.     

Rotating machinery fault diagnosis based on convolutional neural network and infrared thermal imaging

Rotating machinery is widely applied in industrial applications. Fault diagnosis of rotating machinery is vital in manufacturing system, which can prevent catastrophic failure and reduce financial losses. Recently, Deep Learning (DL)-based fault diagnosis method becomes a hot topic. Convolutional Neural Network (CNN) is an effective DL method to extract the features of raw data automatically. This paper develops a fault diagnosis method using CNN for InfRared Thermal (IRT) image. First, IRT technique is utilized to capture the IRT images of rotating machinery. Second, the CNN is applied to extract fault features from the IRT images. In the end, the obtained features are fed into the Softmax Regression (SR) classifier for fault pattern identification. The effectiveness of the proposed method is validated using two different experimental data. Results show that the proposed method has a superior performance in identification various faults on rotor and bearings comparing with other deep learning models and traditional vibration-based method.     

夜气辉对天基光学碎片探测的影响分析

设计并完成了夜气辉背景下的天基碎片观测试验，获取了综合谱段的观测数据。基于观测数据进行夜气辉的辐射特性及其对天基碎片探测的影响分析。结果表明，夜气辉辐射随纬度和高度呈现一定的分布特点，这些特点均符合夜气辉的理论分布规律。在约90 km处辐射最强，亮度可达到单位积分时间每平方角秒近15星等，这对恒星及碎片提取概率影响较大，其中，13等星的提取概率仅为40.5%。     

虚拟多触角探测的高超声速滑翔飞行器再入机动制导

针对高超声速滑翔飞行器再入过程中面对的多约束问题，提出一种基于虚拟多触角探测的路航点规划机动制导策略。该机动制导策略通过飞行器最大转弯轨迹计算速度-剩余地面距离-航向角约束，在分段定点模式中发出多条粗略预测触角，引用触角末端反馈的信息计算优先级以确定临时路航点；同时在机动制导模式中发出精细探测触角，计算触角末端信息优先级，经倾侧角延时滤波器得出控制指令，对飞行器进行机动制导。基于多触角探测的路航点规划机动制导策略，降低了三触角机动制导方法中的计算时间；同时，4种典型禁飞区条件下的仿真结果表明，该策略能够有效稳定地解决机动制导过程中的多约束问题。     

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.     

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。     

微带线不均匀区的平面格林函数分析程序设计

讨论了微带线不均匀区的平面格式函数分析法,应用精确的计算公式编制程序,并考虑了高次模效应,分析了边缘场效应,引入了动态有效介电常数,提高了计算精度,同时给出了提高计算速度的方法。     

探测复合材料层板基体裂纹的实验技术

介绍探测复合材料层板基体裂纹的三种实验技术:声波发射探测,超声波C扫描和复制带记录。在试验各阶段,应充分利用每种试验方法的优点,使每个试件比常规试验获取更多的试验数据,包括声波发射探测响应图,超声波对整个试件宽度扫描成像,以及沿着试件侧面厚度上的复制带获取图像。最初由声波发射显示试件加载期间基体裂纹的开始形成,通过超声波扫描能清晰分辨出第一条基体裂纹的出现;随着基体裂纹的发展,可综合应用三种实验技术,确定对基体断裂的评估。根据试验结果,对这三种实验技术作了评价。     

运动干涉检测的模糊逻辑控制

在采用最大相对速度－距离法的基础上,引入模糊逻辑控制时间裕度,使任意两次检测间的时间间隔适当增大。该方法不仅减少了检测次数,更主要的是利用模糊逻辑的鲁棒性,减少了误差对检测结果的影响,从而使它无论在效率还是在可靠性方面都有了提高。以运动平面多边形为例,通过不采用、采用、部分采用模糊逻辑控制３种方法加以比较,表明了该方法的可靠性和有效性。     

反作用控制系统推力器失效的外部检测与诊断

通过推进系统外部可测的姿态信息,利用强跟踪滤波器和多模预报估计器,研究了一类非线性系统常值阶跃型故障和间歇性故障的检测与分离问题。对关机失效,利用强跟踪滤波器获得故障效应的估计,检测逻辑采用改进的贝叶斯分类方法,依据推力器失效效应的方向性进行故障单元的分离;对开机失效,采用多模预报,根据相应残差向量范数的比较进行故障的即时无阈值判别,同时完成了故障后系统状态的重构问题。以一类大型航天器的反作用姿态控制系统为例,对其中出现的推力器失效进行了故障识别仿真研究,表明所提方法是有效的。