模拟月壤钻进负载分析与试验研究

月壤与采样机具间的相互作用在月球自主采样器的设计、性能评价、控制和仿真等方面具有重要作用,目前对于月壤与采样机具间相互作用中的钻进负载研究尚不充分。本文基于被动土压力理论,根据不同的土体切削状态,将切削刃前土体分为堆积区和破坏区,重点分析堆积区土体和破坏区土体对总钻头负载的贡献,建立了月壤取心钻头钻进松散土体的钻进负载模型。HIT 2型取心钻头和HIT\|LS1#模拟月壤的钻进试验结果表明,钻进负载理论模型与实际情况具有较高的吻合度。     

多轴联动条件下插补速度实时可调的前瞻控制算法

针对目前多轴联动条件下S形加减速算法复杂,一条插补线段内最大进给速度不能实时可调的问题,提出了一种插补速度实时可调的前瞻控制算法。算法首先根据机床特性和线段夹角建立了小线段衔接处进给速度的约束条件,然后采用加速度跟随原理提出了最大进给速度连续可调的S形加减速控制方法,在此基础上设计了一种加速度自适应调整的前瞻处理算法。该算法在不降低轨迹插补精度的前提下,能以最大的速度通过线段的转接点,从而使整个线段插补过程具有高度的柔性和快速性,能满足现代数控系统对前瞻处理的实时性要求。结果表明该算法有效降低了机床运动时的振动,与传统速度规划算法相比,同等加工条件下,加工效率明显提高,工件表面质量也得到改善。     

挠性航天器姿态机动的变论域自整定模糊PID控制

建立了带有太阳翼的挠性航天器的姿态动力学模型,应用改进的罗德里格参数来描述姿态运动学模型。针对挠性航天器模型参数不确定性和环境干扰等问题,提出了变论域自整定模糊比例积分微分(PID)控制方案,构建了计算简单并且可以达到控制精度的伸缩因子。基于Matlab/Simulink进行了仿真验证,结果表明,变论域自整定模糊PID 控制响应速度比传统PID控制、模糊PID控制快350s,且无超调,不仅能够使航天器完成对目标姿态的机动,而且能够有效地抑制挠性太阳翼的振动。     

中继卫星S/Ka双频地面站天线共用跟踪接收机

论述了Ka频段圆波导TE11和TE21模自跟踪体制和S频段正十字排列四喇叭自跟踪体制共用两信道自跟踪接收机问题.导出了来波及地面天线S频段和、差信道极化特性引起的角误差电压的交叉耦合系数公式.还可以进一步使S/Ka两个频段共用一套能跟踪（直接序列）扩频信号源的伪单脉冲（单信道单脉冲）自跟踪接收机.     

Ka频段有源瓦片天线的设计

有源相控阵天线广泛应用于弹载、星载、舰载、机载雷达及电子对抗、汽车自动驾驶等领域。按照T/R组件和天线的集成方式不同,相控阵天线分为瓦片式结构和砖块式结构。传统的砖式结构,多路合成体积过大、损耗过高且造价昂贵,采用微组装工艺生产,量产良品率低。介绍了一种瓦片式有源天线,给出了天线样机的典型性能指标,工艺实现简单,具有轻型化、小型化、低成本及高可靠等特点。针对瓦片天线设计中的难点、垂直互联技术和复杂的馈电网络,结合理论分析进行了仿真设计。为了验证相控阵天线的性能,在微波暗室对天线进行了测试。测试结果表明,设计的瓦片天线法向EIRP＞31dBW,G/T＞-4dB/K,扫描至45°时EIRP＞29dBW,G/T＞-6dB/K,发射状态功耗小于10W,接收状态功耗小于6W。     

一种Ka频段单通道调制器的设计与实现

随着航天事业的不断发展,卫星平台及有效载荷的轻量化、小型化是未来航天系统的发展趋势。单通道单脉冲跟踪系统在航天器中有着广泛的应用,而单通道调制器是单通道单脉冲跟踪系统的重要组成部分。为顺应星载自跟踪系统轻量化、小型化发展趋势,根据工程化要求,采用多芯片微组装技术,通过合理的系统分析和仿真设计,在厚度为0.254mm、相对介电常数为2.2的ROGERS 5880介质基板上设计实现了一种Ka频段单通道调制器。该调制器实现了小型化和集成化,采用BJ260波导作为输入,其和通道增益大于30dB,噪声系数优于2.5dB,载波抑制大于50dB,调制抑制大于30dB,经过地面各项试验及在轨飞行验证,其各项指标满足要求。     

锂氟化碳电池对火星探测任务工况适应性研究

锂氟化碳电池在固体正极体系一次电池中拥有最高的理论比能量(约2180 W·h·kg-1),特别适合对载荷质量要求苛刻的深空探测任务.我国首个火星探测器"天问一号"在其着陆巡视器内部使用了一组锂氟化碳电池用于完成进入—下降—着陆段的供电任务.文章提炼锂氟化碳电池与深空探测应用密切相关的4项基本特性,根据火星探测任务的特点...     

基于IFS和IPSO算法的干扰资源分配方法

针对多干扰系统同时干扰多部雷达的干扰资源分配问题,提出一种基于直觉模糊集(IFS)和改进粒子群优化(IPSO)算法相结合的干扰资源分配方法。利用己方无源探测系统获得的敌方雷达参数,根据IFS理论得到敌方雷达的威胁系数;整合数据库中战场的己方干扰系统与敌方雷达系统信息,从空域、频域、极化方式和干扰样式4个方面定义了匹配度,表示己方干扰系统对敌方雷达系统的干扰效率,得到匹配度矩阵,结合敌方雷达威胁系数建立干扰目标函数;提出一种自适应调整权重、异步变化学习因子、针对离散问题的IPSO算法,并引入补偿粒子进行盲区搜索,求解出最佳干扰决策。仿真表明,本文提出的干扰资源分配方法相较于传统算法最优解正确率更高,且实时性更好。     

Fault diagnosis of an intelligent hydraulic pump based on a nonlinear unknown input observer

Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system (IHPS) based on a nonlinear unknown input observer (NUIO) is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS.     

Super-resolution reconstruction of astronomical images using time-scale adaptive normalized convolution

In this work, we describe a new multiframe Super-Resolution (SR) framework based on time-scale adaptive Normalized Convolution (NC), and apply it to astronomical images. The method mainly uses the conceptual basis of NC where each neighborhood of a signal is expressed in terms of the corresponding subspace expanded by the chosen polynomial basis function. Instead of the conventional NC, the introduced spatially adaptive filtering kernel is utilized as the applicability function of shape-adaptive NC, which fits the local image structure information including shape and orientation. This makes it possible to obtain image patches with the same modality, which are collected for polynomial expansion to maximize the signal-to-noise ratio and suppress aliasing artifacts across lines and edges. The robust signal certainty takes the confidence value at each point into account before a local polynomial expansion to minimize the influence of outliers. Finally, the temporal scale applicability is considered to omit accurate motion estimation since it is easy to result in annoying registration errors in real astronomical applications. Excellent SR reconstruction capability of the time-scale adaptive NC is demonstrated through fundamental experiments on both synthetic images and real astronomical images when compared with other SR reconstruction methods.