A comprehensive survey on the methods of angle of attack measurement and estimation in UAVs

Angle of Attack (AOA) is a crucial parameter which directly affects the aerodynamic forces of an aircraft. The measurement of AOA is required to ensure a safe flight within its designed flight envelop. This paper intends to summarise a comprehensive survey on the measurement techniques and estimation methods for AOA, specifically in Unmanned Aerial Vehicle (UAV) applications. In the case of UAVs, weight constraint plays a major role as far as sensor suites are concerned. This results in selecting a suitable estimation method to extract AOA using the available data from the autopilot. The most feasible and widely employed AOA measurement technique is by using the Multi-Hole Probes (MHPs). The MHP measures the AOA regarding the pressure variations between the ports. Due to the importance of MHP in AOA measurement, the calibration methods for the MHP are also included in this paper. This paper discusses the AOA measurement using virtual AOA sensors, their importance and the operation.     

Semi-supervised gear fault diagnosis using raw vibration signal based on deep learning

In aerospace industry, gears are the most common parts of a mechanical transmission system. Gear pitting faults could cause the transmission system to crash and give rise to safety disaster. It is always a challenging problem to diagnose the gear pitting condition directly through the raw signal of vibration. In this paper, a novel method named augmented deep sparse autoencoder (ADSAE) is proposed. The method can be used to diagnose the gear pitting fault with relatively few raw vibration signal data. This method is mainly based on the theory of pitting fault diagnosis and creatively combines with both data augmentation ideology and the deep sparse autoencoder algorithm for the fault diagnosis of gear wear. The effectiveness of the proposed method is validated by experiments of six types of gear pitting conditions. The results show that the ADSAE method can effectively increase the network generalization ability and robustness with very high accuracy. This method can effectively diagnose different gear pitting conditions and show the obvious trend according to the severity of gear wear faults. The results obtained by the ADSAE method proposed in this paper are compared with those obtained by other common deep learning methods. This paper provides an important insight into the field of gear fault diagnosis based on deep learning and has a potential practical application value.     

Substitution of satellite-based land surface temperature defective data using GSP method

Land surface temperature (LST) as an important environmental variable provides valuable information for earth environmental system modelling. Currently, LST is obtained through satellite thermal sensors at various spatial and temporal resolutions. Although spatially continuous satellite-based LST measurements are intended to overcome the shortcomings of sparse ground-based LST measurements, LST images often contain anomalous values due to the existence of clouds or sensor malfunctioning. The problem becomes more serious where the users deal with high spatial resolution characterized by low temporal resolution. This study examines the capability of a newly developed graph signal processing (GSP) method using two-dimensional single-date thermal data. For this purpose, four Landsat/TIRS datasets are analyzed. The data of five elliptical regions on thermal images are eliminated and then reconstructed through the GSP method and using the LST values of the enclosing rectangles containing the ellipsoids. The results indicate that the temperature variation determined by the GSP method generally conforms to the original image LST values. According to a correlation test conducted on the original image LST and those obtained through the GSP method, the values vary from 58% to 95%, which is an above-the-average rate (RMSE from 0.69 to 2.27). The statistical analysis of the original image LST in both the elliptical regions and the enclosing rectangles containing the ellipsoids indicates that an increase in the variance of LST data causes an increased error in the calculation of temperature by the GSP method, and vice versa. The results of the analysis of variance (ANOVA) and Duncan test indicated that an increase in the number of the non-zero spectral bins would result in increased RMSE values for all the dates and the regions. Moreover, the model errors were significant at the 0.05 level across all the image date and five elliptical study regions. Based on the results, the use of this method is recommended for the reconstruction of LST missing values, where dissimilarity of atmospheric conditions limits the use of other methods that depend on the time series data of various dates and a great deal of data calculation.     

FDI飞机舵面损伤故障全局检测的非线性数学模型

阐述了飞机在单舵面损伤故障下 ,建立故障状态下的数学模型 ,以及同样输入条件下飞机正常运动时的数学模型 ,得到飞机在相同飞行条件下损伤时的气动系数和无损伤正常时的气动系数 ,最终得到气动系数的残差。这将为以后飞机过载残差和角加速度残差奠定基础。论文中结合一定的算例给予证实推论的正确性。     

燃烧火焰温度分布重建结果误差分析

分析了采用辐射型CT算法的燃烧火焰温度发布重建结果误差产生的原因，给出了解决方法。     

FET振荡器注入锁相伏特拉级数分析

应用伏特拉级数法分析了电容耦合ＦＥＴ振荡系统在外加信号下的注入锁定现象，推导出输出信号和注入锁定带宽表达式。与一般非线性系统分析方法相比，伏特拉级数法在建立好系统模型后只需进行代数运算，从而避开了求解非线性，非齐次高阶微分方程的复杂过程。     

世界贸易组织与航空产品包装

论述了我国加入世界贸易组织后，如何搞好航空产品的包装和包装标准化工作，以提高航空工业军品和民品在国际市场的竞争能力。     

河北省高校农村生源学生思想现状调查研究

河北省农村人口占总人口的79％，是一个比较典型的农业大省。农村生源大学生，是河北省在校大学生的重要组成部分，占生源的最大比例。大学生是宝贵的人才资源，他们的素质尤其是思想政治素质如何，他们能否成为社会主义事业的合格建设者和可靠接班人，是一个非常重要的问题。因而，科学分析和把握他们的思想政治状况，将会增强我们把握大学生思想脉搏的准确性和说服力。为此笔者选取了河北省八个地市的不同高校，进行了问卷调查、座谈和访谈。对河北省农村生源大学生的思想现状进行了调查。通过统计软件的录入和整理，统计结果比较真实地显示了当前河北省农村生源大学生的思想现状。     

高速低压差分信号（LVDS）器件应用设计方法研究

随着高速LVDS器件得到广泛应用，在高速信号使用LVDS传输时，信号传输线路问题、信号传输波形的最佳化成为非常重要的课题之一。由于印制电路板的布局布线直接影响信号传输质量，因此利用仿真对印制板分析成为设计上不可缺少的手段。有鉴于此，文章深入探讨了高速电路的设计，总结出设计技巧。     

一种卫星间跟瞄方向的控制策略与实现

进行自由空间的光通信或空间对抗，需要在卫星间实现精确的跟踪与瞄准。因为地面测控站的设置非常有限，指令与数据注入的范围受到很多限制，所以要求这种跟瞄在很多时候是无主控制状态下完成的。提出了一种利用在地面测控站的范围内向星上数管中心注入目标卫星、本体卫星的轨道参数，其它时间依靠自主导航飞行和GPS修正的方法，结合本体星的姿态测量、振动测量实现卫星瞄准指向的方位角与俯仰角的精确控制的方法，提高了在地面站无法注入指令与数据时卫星的捕获概率。通过仿真，将计算结果与卫星仿真工具软件STK的数据进行比较，结果一致。最后在嵌入式DSP平台上实现了这一策略。