平面近场测试中误差的分析

首先介绍了暗室中主要的误差项,然后通过实际测试的方式,分析了其中四项误差对超低副瓣天线-50dB副瓣的不确定度.结果对超低副瓣天线副瓣的误差分析有一定的参考意义,有助于天线设计师了解超低副瓣天线测试中误差项对副瓣的影响量级.     

Evaluation and improvement of coastal GNSS reflectometry sea level variations from existing GNSS stations in Taiwan

Global sea level rise due to an increasingly warmer climate has begun to induce hazards, adversely affecting the lives and properties of people residing in low-lying coastal regions and islands. Therefore, it is important to monitor and understand variations in coastal sea level covering offshore regions. Signal-to-noise ratio (SNR) data of Global Navigation Satellite System (GNSS) have been successfully used to robustly derive sea level heights (SLHs). In Taiwan, there are a number of continuously operating GNSS stations, not originally installed for sea level monitoring. They were established in harbors or near coastal regions for monitoring land motion. This study utilizes existing SNR data from three GNSS stations (Kaohsiung, Suao, and TaiCOAST) in Taiwan to compute SLHs with two methods, namely, Lomb–Scargle Periodogram (LSP)-only, and LSP aided with tidal harmonic analysis developed in this study. The results of both methods are compared with co-located or nearby tide gauge records. Due to the poor quality of SNR data, the worst accuracy of SLHs derived from traditional LSP-only method exceeds 1?m at the TaiCOAST station. With our procedure, the standard deviations (STDs) of difference between GNSS-derived SLHs and tide gauge records in Kaohsiung and Suao stations decreased to 10?cm and the results show excellent agreement with tide gauge derived relative sea level records, with STD of differences of 7?cm and correlation coefficient of 0.96. In addition, the absolute GNSS-R sea level trend in Kaohsiung during 2006–2011 agrees well with that derived from satellite altimetry. We conclude that the coastal GNSS stations in Taiwan have the potential of monitoring absolute coastal sea level change accurately when our proposed methodology is used.     

基于电力综合集成的多绕组双流发电机技术分析

为解决采用传统发电机的移动电站输出电源种类单一,而采用多台发电机又会造成底盘过载影响机动性的问题,文章基于电力综合集成技术,分析研究实现发电机的双流发电的关键技术,突破发电机多绕组发电及励磁解耦等难题,减小了电机体积、降低了电机重量,有利于移动电站的多功能化与小型化设计。     

基于自适应径向基网络的舰船RCS统计特征识别方法

文章采用舰船RCS频域起伏序列的均值、标准差为识别特征向量,利用提出的基于样本密度的自适应径向基网络,进行舰船分类识别研究。自适应径向基网络采用改进的自适应PSO方法估计样本密度最优邻域半径,实现径向基网络中心的自适应选择。改进的自适应PSO方法采用能反映样本聚类特点的BWP指标为适应度评价函数,采用快慢结合的高斯自适应惯性权重调节策略,提高了最优样本密度邻域半径的搜索速度和精度。实验结果表明,自适应径向基网络能自适应获得径向基网络最优识别率对应的RBF中心及其位置分布,减少了对建模人员经验的依赖,提高了反舰导弹对舰船类型的识别分类能力。     

基于Visual Basic的互感器负荷箱测量仪校准系统的实现

为解决互感器负荷箱测量仪同相分量和正交分量的校准问题,在分析互感器负荷箱测量仪工作原理的基础上,设计了基于电子/电工组合式的互感器负荷箱测量仪校准装置,并简要说明装置电工部分、电子部分以及上位机软件的实现。经省级计量研究院验证结果表明,该装置校准结果符合0.2级要求,可作为标准装置解决1级互感器负荷箱测量仪量值溯源问题。     

Drag Reducing and Increasing Mechanism on Triangular Riblet Surface

Drag reducing and increasing mechanism on riblet surface has been studied through computational fluid dynamics(CFD).Drag reduction is achieved through the optimization of riblet geometry which would affect flow structure inside riblet grooves.Force and flow structure on riblet surface are analyzed and compared with those of smooth surface based on the k-εturbulence model.Drag reducing and increasing mechanism is proved to be related to microvortexes induced inside riblets which lead to Reynolds shear stress reduction significantly and is considered to be the dominant factor resulting in wall friction reduction.Simulation results also show that the pressure drag generating from the deviation of static pressure on the front and rear ends of riblets occurs and grows exponentially with Mach number,which can cause drag increasing.Furthermore,near-wall vortical structures,Reynolds shear stress and static pressure on riblet surfaces are also analyzed in detail.     

在实时嵌入式环境下利用电子盘实现大容量数据记录的软件设计研究

嵌入式环境和实时操作系统目前广泛应用于航空领域。本文在介绍嵌入式系统的基础上,重点对实时多任务环境下大容量数据记录的实现方式进行了研究和利用,最后展望了电子盘实时多任务系统中记录大容量数据的前景。     

An Improved Nonlinear Dynamic Inversion Method for Altitude and Attitude Control of Nano Quad-Rotors under Persistent Uncertainties

Nonlinear dynamic inversion(NDI)has been applied to the control law design of quad-rotors mainly thanks to its good robustness and simplicity of parameter tuning.However,the weakness of relying on accurate model greatly restrains its application on quad-rotors,especially nano quad-rotors(NQRs).NQRs are easy to be influenced by uncertainties such as model uncertainties(mainly from complicated aerodynamic interferences,strong coupling in roll-pitch-yaw channels and inaccurate aerodynamic prediction of rotors)and external uncertainties(mainly from winds or gusts),particularly persistent ones.Therefore,developing accurate model for altitude and attitude control of NQRs is difficult.To solve this problem,in this paper,an improved nonlinear dynamic inversion(INDI)method is developed,which can reject the above-mentioned uncertainties by estimating them and then counteracting in real time using linear extended state observer(LESO).Comparison with the traditional NDI(TNDI)method was carried out numerically,and the results show that,in coping with persistent uncertainties,the INDI-based method presents significant superiority.     

基于人工神经网络的停机坪安全预警研究

停机坪是机场的重要组成部分,停机坪安全是机场安全关注的重点。影响停机坪安全作业的要素有很多,通过对这些要素进行监控和预警,可以减少停机坪的安全隐患,保证机场正常运行。根据济南遥墙机场的主要数据,运用因子分析法对影响停机坪安全的主要因素进行分类,提取公共因子。并运用人工神经网络（ANN）方法,对这些公共因子进行神经网络训练和预测分析,最终得到遥墙机场停机坪的安全情况。