基于SAN构建高可用实时存储系统

介绍SAN网络存储技术及其拓扑结构,针对某飞控中心数据存储系统的实际需求,设计和实现一个SAN存储结构上的高可用实时可扩展集群存储方案,并详细描述通过软、硬件结合实现冗余数据路径、故障切换、实时存储和查询的方法。     

Performance improvement of licklider transmission protocol in complex deep space networks based on parameter optimization

A reasonable parameter configuration helps improve the data transmission performance of the Licklider Transmission Protocol (LTP). Previous research has focused mainly on parameter optimization for LTP in simplified scenarios with one to two hops or multihop scenarios with a custody mechanism of the Bundle Protocol (BP). However, the research results are not applicable to communications in Complex Deep Space Networks (CDSNs) without the custody mechanism of BP that are more suitable for deep space communications with LTP. In this paper, we propose a model of file delivery time for LTP in CDSNs. Based on the model, we propose a Parameter Optimization Design Algorithm for LTP (LTP-PODA) of configuring reasonable parameters for LTP. The results show that the accuracy of the proposed model is at least 6.47% higher than that of the previously established models based on simple scenarios, and the proposed model is more suitable for CDSNs. Moreover, the LTP parameters are optimized by the LTP-PODA algorithm to obtain an optimization plan. Configuring the optimization plan for LTP improves the protocol transmission performance by at least 18.77% compared with configuring the other parameter configuration plans.     

Cooperative fault detection and recovery in the GNSS positioning of mobile agent swarms based on relative distance measurements

Relative measurements are exploited to cooperatively detect and recover faults in the positioning of Mobile Agent(MA) Swarms(MASs). First, a network vertex fault detection method based on edge testing is proposed. For each edge, a property that has a functional relationship with the properties of its two vertices is measured and tested. Based on the edge testing results of the network, the maximum likelihood principle is used to identify the vertex fault sources. Second, an edge distance testing...     

耐高温复合材料在火星探测器着陆器减速伞筒盖结构上的应用

针对火星探测器着陆巡视器减速伞筒盖结构在轨运行耐温度交变、辐照等空间环境和再入过程耐温度冲击性能需求,重点开展了筒盖复合材料耐温匹配性、力学性能、耐空间环境性能以及制件成型工艺研究。结果表明,选用J-168-1胶黏剂、J-245胶黏剂及T300/QY8911复合材料制备的试件通过各项性能试验考核,均能满足筒盖结构的设计指标要求。筒盖产品力学性能稳定,成型工艺可行性良好,最高瞬时使用温度可达200℃,经历空间环境模拟后力学性能保持率均在80%以上,耐高温、耐空间环境性良好。产品已成功装星发射,并在着陆巡视器落火阶段成功弹出分离,圆满完成使命。     

FY-2C星地面应用分系统指令与数据获取站

介绍了风云二号(FY-2)C星地面应用分系统数据与指令接收站(CDAS)的主要技术指标、工作流程,以及与C星的星地接口与地面应用分系统其他部分的接口.说明了CDAS的天伺馈、信道、图像获取(IAS)、三点测距(TRRR)、数据收集(DCP)、遥测遥控(TT&C)、卫星模拟器、标校、时间统-、低速信息传输(LRIT)信息编码与发送等子系统的组成与功能.阐述了C星CDAS的设计原则,以及用群调技术实现DCP的数据解调、用扩频伪码进行TRRR定位、图像处理、TT&C增加图形化界面控制、正交相移键控(QPSK)解调器抗长连"1"功能等关键技术.在轨测试和试运行期间,C星的CDAS不仅解决暴露的问题,而且进行适应性调整.验收前测试结果表明,其功能及技术指标满足业务运行要求,设备工作正常、性能稳定.     

增强神经网络辨识模型泛化能力的研究

神经网络(Artificial Neural Network,ANN)辨识模型的泛化能力是其最主要的性能之一,增强ANN模型的泛化能力也是近年来国内外有关专家学者研究的重点问题。大量研究表明,ANN模型泛化能力的改善与很多因素相关联,其中恰当的性能指标函数设计是一个重要影响因素。文中在分析常见的基于均方误差最小原则的性能指标函数基础上,通过加入ANN辨识模型权值间的延迟信息,进而获得一种改进型性能指标函数。通过仿真,验证了所设计的改进型性能指标函数对增强ANN辨识模型的泛化能力是有效的。     

涡轮动叶部分吸力侧肩壁凹槽状叶顶气热和冷却性能研究

为了获取高性能的燃气涡轮动叶叶顶结构和气膜冷却布局，采用数值求解三维Reynolds-Averaged Navier-Stokes (RANS) 方程和标准 湍流模型的方法研究了涡轮动叶部分吸力侧肩壁的凹槽状叶顶气热和冷却性能。数值模拟得到的动叶平叶顶传热系数与实验数据吻合良好，验证了数值方法的准确性。对比0.95吹风比时动叶凹槽状叶顶沿中弧线和近压力侧布置的2种气膜冷却布局的叶顶泄漏流动形态、传热系数和气膜冷却有效度，指出近压力侧的气膜冷却布局B的总压损失大于沿中弧线的气膜冷却布局A；但近压力侧的气膜冷却布局B具有更好的冷却效果。基于近压力侧气膜冷却布局的凹槽状叶顶结构，通过切除尾缘处不同轴向长度的吸力侧肩壁，设计了5种不同的部分吸力侧肩壁的叶顶结构。结果表明：切除10%吸力侧肩壁的Case 7能有效降低总压损失，平均总压损失系数相比完整肩壁的Case 2降低了6.3%；叶顶净热流密度减少和传热系数分布与Case 2基本相同，尾缘处的冷却效率因冷气受到压制附着于叶顶而提高。     

Surrogate role of machine learning in motor-drive optimization for more-electric aircraft applications

Motor drives form an essential part of the electric compressors, pumps, braking and actuation systems in the More-Electric Aircraft (MEA). In this paper, the application of Machine Learning (ML) in motor-drive design and optimization process is investigated. The general idea of using ML is to train surrogate models for the optimization. This training process is based on sample data collected from detailed simulation or experiment of motor drives. However, the Surrogate Role (SR) of ML may vary for different applications. This paper first introduces the principles of ML and then proposes two SRs (direct mapping approach and correction approach) of the ML in a motor-drive optimization process. Two different cases are given for the method comparison and validation of ML SRs. The first case is using the sample data from experiments to train the ML surrogate models. For the second case, the joint-simulation data is utilized for a multi-objective motor-drive optimization problem. It is found that both surrogate roles of ML can provide a good mapping model for the cases and in the second case, three feasible design schemes of ML are proposed and validated for the two SRs. Regarding the time consumption in optimizaiton, the proposed ML models can give one motor-drive design point up to 0.044 s while it takes more than 1.5 mins for the used simulation-based models.     

6G service-oriented space-air-ground integrated network: A survey

As an indispensable component of the emerging 6G networks, Space-Air-Ground Integrated Networks (SAGINs) are envisioned to provide ubiquitous network connectivity and services by integrating satellite networks, aerial networks, and terrestrial networks. In 6G SAGINs, a wide variety of network services with the features of diverse requirements, complex mobility, and multi-dimensional resources will pose great challenges to service provisioning, which urges the development of service-oriented SAGINs. In this paper, we conduct a comprehensive review of 6G SAGINs from a new perspective of service-oriented network. First, we present the requirements of service-oriented networks, and then propose a service-oriented SAGINs management architecture. Two categories of critical technologies are presented and discussed, i.e., heterogeneous resource orchestration technologies and the cloud-edge synergy technologies, which facilitate the interoperability of different network segments and cooperatively orchestrate heterogeneous resources across different domains, according to the service features and requirements. In addition, the potential future research directions are also presented and discussed.     

Adaptive cubature Kalman filter with the estimation of correlation between multiplicative noise and additive measurement noise

Mobile robots are often subject to multiplicative noise in the target tracking tasks, where the multiplicative measurement noise is correlated with additive measurement noise. In this paper,first, a correlation multiplicative measurement noise model is established. It is able to more accurately represent the measurement error caused by the distance sensor dependence state. Then, the estimated performance mismatch problem of Cubature Kalman Filter(CKF) under multiplicative noise is analyzed. An i...