插装式液控能源选择阀的设计与分析

针对液压系统油源的安全性及可靠性问题，提出油源冗余设计方法，即多油源供给多负载，当某一油源发生故障时能源选择阀切断故障油源，由其他油源给负载提供基本液压能源，系统能完成必须的服役性能。针对液压系统能源选择阀存在的频繁换向与振动问题，提出一种插装式液控能源选择阀，其先导阀采用锥阀和可变阻尼形式，主阀采用三台肩且终端有缓冲功能的滑阀。建立了插装式液控能源选择阀的数学模型，分析了能源选择阀在两种模拟故障下的切换压力及切换时间、油源压力脉动等特性。理论分析结果表明，油源压力阶跃和线性变化时，某能源选择阀切换时间分别为5 ms和7 ms。当压力发生波动时，主阀不会发生振动，还可通过液控先导阀结构设计来控制切换压力和回复压力大小。     

复杂动态环境下无人飞行器动态避障近似最优轨迹规划

针对复杂动态环境下无人飞行器的动态障碍规避问题，基于合理假设建立了无人飞行器和动态障碍的运动学模型，并综合考虑无人飞行器飞行过程中的终端约束、控制输入约束、安全避障约束等，以能量最少为性能指标构建动态避障问题数学描述。之后，针对终端约束和控制输入约束，依据优化模型预测静态规划算法(OMPSP)生成初始轨迹；针对动态避障问题的不等式约束，引入松弛变量并结合滑模变结构控制方法设计松弛变量动力学，实现对一个、多个或同时多个动态障碍的安全规避；最后，依据有限时间微分动态规划(RHDDP)算法进行轨迹优化，获得满足上述各种约束并能规避动态障碍的近似最优轨迹。     

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.     

Deorbiter CubeSat mission design

This paper presents the mission design for a CubeSat-based active debris removal approach intended for transferring sizable debris objects from low-Earth orbit to a deorbit altitude of 100 km. The mission consists of a mothership spacecraft that carries and deploys several debris-removing nanosatellites, called Deorbiter CubeSats. Each Deorbiter is designed based on the utilization of an eight-unit CubeSat form factor and commercially-available components with significant flight heritage. The mothership spacecraft delivers Deorbiter CubeSats to the vicinity of a predetermined target debris, through performing a long-range rendezvous maneuver. Through a formation flying maneuver, the mothership then performs in-situ measurements of debris shape and orbital state. Upon release from the mothership, each Deorbiter CubeSat proceeds to performing a rendezvous and attachment maneuver with a debris object. Once attached to the debris, the CubeSat performs a detumbling maneuver, by which the residual angular momentum of the CubeSat-debris system is dumped using Deorbiter’s onboard reaction wheels. After stabilizing the attitude motion of the combined Deorbiter-debris system, the CubeSat proceeds to performing a deorbiting maneuver, i.e., reducing system’s altitude so much so that the bodies disintegrate and burn up due to atmospheric drag, typically at around 100 km above the Earth surface. The attitude and orbital maneuvers that are planned for the mission are described, both for the mothership and Deorbiter CubeSat. The performance of each spacecraft during their operations is investigated, using the actual performance specifications of the onboard components. The viability of the proposed debris removal approach is discussed in light of the results.     

A progressive approach to predict shot peening process parameters for forming integral panel of Al7050-T7451

In this paper, a progressive approach to predict the multiple shot peening process parameters for complex integral panel is proposed. Firstly, the invariable parameters in the forming process including shot size, mass flow, peening distance and peening angle are determined according to the empirical and machine type. Then, the optimal value of air pressure for the whole shot peening is selected by the experimental data. Finally, the feeding speed for every shot peening path is predicted by regression equation. The integral panel part with thickness from 2 mm to 5 mm and curvature radius from 3200 mm to 16000 mm is taken as a research object, and four experiments are conducted. In order to design specimens for acquiring the forming data, one experiment is conducted to compare the curvature radius of the plate and stringer-structural specimens, which were peened along the middle of the two stringers. The most striking finding of this experiment is that the outer shape error range is below 3.9%, so the plate specimens can be used in predicting feeding speed of the integral panel. The second experiment is performed and results show that when the coverage reaches the limit of 80%, the minimum feeding speed is 50 mm/s. By this feeding speed, the forming curvature radius of the specimens with different thickness from the third experiment is measured and compared with the research object, and the optimal air pressure is 0.15 MPa. Then, the plate specimens with thickness from 2 mm to 5 mm are peened in the fourth experiment, and the measured curvature radius data are used to calculate the feeding speed of different shot peening path by regressive analysis method. The algorithm is validated by forming a test part and the average deviation is 0.496 mm. It is shown that the approach can realize the forming of the integral panel precisely.     

一种基于VPL 的元器件快速建模方法

为了更好地落实航空电子模块的可制造性设计审查工作,结合航空电子模块产品特点和技术要求,建设了基于Valor软件的PCB/PCBA设计与检测自动化分析系统.元器件模型库作为该系统的必要组成部分,其覆盖范围和数据精度对审查结果至关重要.本文将从元器件模型库建设必要性、建设过程和建模工艺要求三个方面进行阐述,并提出一种基于Valor VPL的元器件快速建模方法,应用结果表明,该方法能够高效构建满足系统审查精度的元器件模型,使大规模元器件模型库的建设成为可能.     

基于双滤波器的高精度目标跟踪估计方法

针对连续推力的合作航天器，采用双重无迹卡尔曼滤波(DUKF)算法估计其状态和加速度。通过状态滤波器和参数滤波器的配合，提升滤波精度，完成运动状态和参数的估计，从而实现合作目标的运动轨迹跟踪。与合作航天器相比，非合作航天器存在大小未知、发生时刻未知的机动，无法获得加速度，且信息获取和运动状态的估计难度大。针对非合作航天器，基于简化的相对运动方程，结合天基平台获得目标的观测信息，采用两个扩展卡尔曼滤波(EKF)及基于半正焦弦的机动检测策略实现多未知脉冲机动的运动状态的估计。仿真结果表明：相比于无迹卡尔曼滤波（UKF），DUKF在对合作航天器的状态和加速度估计方面具有更快的收敛速度和更高的滤波精度；对于存在未知机动的非合作航天器，通过对比验证机动检测策略与滤波器切换策略相结合的方法的有效性，该方法能够检测到多次机动并且减少误判。     

航天嵌入式软件数组越界缺陷特征研究

根据统计,数组越界是航天嵌入式软件开发过程中出现最多且最容易被遗漏的缺陷类型之一.目前自动化检测数组越界多基于抽象解释、符号执行、程序模型检验等方法,这些方法在误报、漏报、可扩展性等方面的表现依赖于软件及缺陷特征.分析了近三年航天嵌入式软件第三方测试中发现的94个数组越界问题,从缺陷模式和缺陷表现形式两方面分析得出10项航天嵌入式软件数组越界缺陷特征,并提出对设计具体检测方法关键的若干启示.进一步基于这些特征和启示探讨了数组越界检测算法针对中断驱动型程序的改进方向.     

Development and performance evaluation of tropospheric scintillation model on Ku-band satellite link over Akure,Nigeria

Existing amplitude scintillation prediction models often perform less satisfactorily when deployed outside the regions where they were formulated. This necessitates the need to evaluate the performance of scintillation models developed in one region using data data from other regions while documenting their relative errors. Due to its variation with elevation angle, frequency, other link parameters and meteorological factors, we employed three years (January 2016 to December 2018) of concurrently measured satellite radio beacons and tropospheric weather parameters to develop a location-based amplitude scintillation prediction model over the Earth-space path of Akure (7.17^oN, 5.18^oE), South-western Nigeria. The satellite beacon measurement used Tektronix Y400 NetTek Analyzer at 1 s integration time while meteorological parameters, namely; temperature, pressure and relative humidity were measured using Davis Vantage Vue weather station at 1 min integration time. Comparative study of the model’s performance with nine (9) existing scintillation prediction models indicates that the best and worst performing models, in terms of root mean square error (RMSE), are the Statistical Temperature and Refractivity (STN) and direct physical and statistical prediction (DPSP) models with values 11.48 and 51.03 respectively. Also, worst month analysis indicates that April, with respective enhancement and fade values of 0.88 and 0.90 dB for 0.01% exceedance, is the overall worst calendar month for amplitude scintillation.     

Orbit-attitude-vibration coupled dynamics of tethered solar power satellite

A new orbit-attitude-vibration coupled dynamic model of the tethered solar power satellite (Tethered SPS) is established based on absolute nodal coordinate formulation. The Hamilton’s equation of the system is derived by introducing generalized momentum through Legendre transformation. The correctness of the proposed model is verified by an example. The dynamic characteristics of the Tethered SPS are studied using the symplectic Runge-Kutta method. Simulation results show that the orbital radius and the total energy of the system are well preserved. The attitude of the system is unstable when the mass of the bus system is small. However, the attitude stability is dependent on some other parameters of the system, which requires further studies. It is also found that the average tether force/deformation can be roughly estimated by simplifying the solar panel as a particle. The proposed model can be used to study the orbit-attitude-vibration coupled dynamics and control problems.