无人水面艇海洋调查国内应用进展与展望

针对浅水区、污染区、极地等复杂海洋环境，传统海洋调查手段劳动强度高、安全风险大、作业效率低。无人水面艇具备无人、高效等特点，非常适合在上述复杂海洋环境中作业，并于近年来在海洋调查领域中得到了快速发展与广泛应用。从海洋调查领域中无人水面艇的优势、国内外典型的无人水面艇和应用案例入手，深入分析了我国无人水面艇海洋调查的现状，并对未来的技术发展方向进行了展望。实践表明，应用无人水面艇进行海底地形地貌调查的技术已基本成熟，水深数据质量和自主导航精度均可满足规范要求。在未来，须将无人水面艇的应用进一步扩展至物理海洋、海洋生物、海洋化学等专业领域，并加快研制基于可再生能源的长航程无人水面艇，以开展全球性海洋调查。     

飞机变形自动化测量方法研究

为解决以往飞机变形测量模式中人工干预较多,受测量环境影响较大,测量时间长等问题,基于Geo COM技术和RS232,在计算机与全站仪之间进行数据交换,设计了一套自动化测量系统。在测量过程中由标志点的机体理论坐标反算其在当前测站中的极坐标,从而在测量过程中驱动全站仪指向待测点,减少人工瞄准时间,并由计算机实时解算结果数据。经实际飞行试验验证表明,测量时间缩短为原来时间一半,大大提高了工作效率。     

Low-latitude storm time ionospheric predictions using support vector machines

The electromagnetic drift plays an important role in low-latitude storm time ionospheric dynamics. In this study we attempt to utilize the electric field data into ionospheric predictions by using support vector machine (SVM), a promising algorithm for small-sample nonlinear regressions. Taking the disturbance electric field data as input, different SVMs have been trained for three seasonal bins at two stations near the north crest of the Equatorial Ionization Anomaly (EIA). Eighteen storm events are used to check out their predicting abilities. The results show fairly good agreement between the predictions and observations. Compared with STORM, a widely used empirical correlation model, the SVM method brings a relative improvement of 23% for these testing events. Based on this study we argue that the SVM method can improve the storm time ionospheric predictions.     

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。     

可拓模式识别算法中经典域的确定方法

可拓模式识别算法是根据各个关联度的对比来识别最终的模式,其中经典域区间的确定有着重要的作用。传统的经典域确定方法是基于数理统计学的,不适用于小样本数据,数据不完全以及数据分布未知等复杂情况。引入Bootstrap算法,并和传统的方法对比,更精确地确定了经典域区间。     

Wilkinson定理扰动界的改进估计

Wilkinson定理是代数特征值问题中的一个经典定理,文章给出了Wilkinson定理的结果中关于扰动矩阵上界的另一种估计形式,并指出该形式对Wilkinson定理具有一定的改进。     

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.