资源卫星数据收集系统及其应用

简要说明了资源卫星数据收集系统(DCS)的原理、组成和特点,在对分布范围广、参数缓变和传输速率低的数据进行采集方面,资源卫星DCS具有很大的优势和很高的利用价值。结合环保监测应用的需求,对资源卫星DCS应用系统方案进行了详细设计。     

我校生产管理实验室建设的构想

文章通过分析生产运作与质量管理专业实验室建设的必要性与定位,提出了我校本专业实验室建设的主体框架,即由仿真的生产线实验室、专业计算机实验室、多媒体实验室、校内现场管理实验室及企业实训基地组合而成的建设项目,并提出了加强生产运作与质量管理专业实验教师培养的几点建议。     

细晶铸造对K418合金拉伸性能的影响

测试了不同温度下细晶铸造和普通铸造Ｋ４１８合金的拉伸性能。结果表明，细晶铸造明显改善了合金的极限位伸强度和屈服强度，室温和６００℃的合金拉伸强度和晶粒平均直径符合Ｈａｌｌ－Ｐｅｔｃｈ关系。     

航空发动机虚拟自学习控制方法研究

随着人工智能技术的发展，智能航空发动机逐渐成为当今航空领域研究的热点。传统的航空发动机控制对发动机模型的依赖性过强，而基于发动机气热动力学公式的机理建模会引入较大的建模误差，给控制器设计带来困难。对此，提出一种基于强化学习的航空发动机控制虚拟自学习方法，首先利用航空发动机的试验数据通过LSTM 神经网络建立虚拟学习环境，然后采用深度强化学习TD3 算法，在虚拟环境中训练智能控制器，最后采用JT9D 发动机模型验证智能控制器的性能。结果表明：相比于传统PID 控制，智能控制器产生的超调量更小，调节时间更短。     

面向任务的空间信息网络体系结构可重组设计

针对空间信息网络体系结构设计和其使命任务的多重性、多维性的问题,提出了一种体系结构可重组设计方法。首先,介绍了空间信息网络及其体系结构的国内外发展现状,分析了研究空间信息网络体系结构可重组设计的需求。其次,结合空间信息网络的概念、结构和特征,建立了松耦合、兼容性、隔离性和可解构的可重组设计原则。同时,定义了管理中心（RMC）和资源中心（RRC）的内涵,分析了RMC和RRC的运行机制,从目标、拓扑、实体、数据、方案5个维度出发提出了一种形式化的可重组网络体系结构模型,并给出了可重组网络体系结构的实现算法流程。最后,以某反导作战活动为例进行了体系结构可组构设计的案例分析,基于STK平台进行可重组网络的仿真演示,着重展示和验证了可重组设计思想在实践中的具体应用,达到了预期目的。     

Carrier phase prediction method for GNSS precise positioning in challenging environment

Since the signals of global navigation satellite system (GNSS) are blocked frequently in challenging environments, the discontinuous carrier phases seriously affect the application of GNSS precise positioning. To improve the carrier phase continuity, this paper proposes a carrier phase prediction method based on carrier open-loop tracking. In the open-loop tracking mode, the carrier numerically controlled oscillator (NCO) is controlled by the predicted Doppler, but not by the loop filter output. To improve the phase prediction effective time, accurate receiver clock drift estimation is studied in the prediction method. The phase prediction performance is tested on GNSS software receiver. In the phase prediction effective time tests, open-loop processes were set for the tested channel. The test results show that, when some satellite signals are blocked in 15?s, the probability of carrier phase error less than quarter cycles is more than 94%. In the real time kinematic (RTK) positioning tests, some satellite signals are blocked in 10–15?s repeatedly. The test results show that, the carrier phase continuity is basically not affected by the signal interruption, and the RTK can almost keep continuous centimeter-level positioning accuracy without re-fixing the integer ambiguity.     

A drilling tool design and in situ identification of planetary regolith mechanical parameters

The physical and mechanical properties as well as the heat flux of regolith are critical evidence in the study of planetary origin and evolution. Moreover, the mechanical properties of planetary regolith have great value for guiding future human planetary activities. For planetary subsurface exploration, an inchworm boring robot (IBR) has been proposed to penetrate the regolith, and the mechanical properties of the regolith are expected to be simultaneously investigated during the penetration process using the drilling tool on the IBR. This paper provides a preliminary study of an in situ method for measuring planetary regolith mechanical parameters using a drilling tool on a test bed. A conical-screw drilling tool was designed, and its drilling load characteristics were experimentally analyzed. Based on the drilling tool-regolith interaction model, two identification methods for determining the planetary regolith bearing and shearing parameters are proposed. The bearing and shearing parameters of lunar regolith simulant were successfully determined according to the pressure-sinkage tests and shear tests conducted on the test bed. The effects of the operating parameters on the identification results were also analyzed. The results indicate a feasible scheme for future planetary subsurface exploration.     

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。