应用加权中值滤波法检测薄壁梁式挠性器件下摆量

应用加权中值滤波法对薄壁梁式挠性器件下摆量进行高准确度CCD检测。薄壁梁式挠性器件在测量过程中测量图像存在高频抖动现象,因此测量准确度不高,运用加权中值滤波后使用最小二乘法细分技术,可以在实现提高测量准确度的同时,消除高频抖动带来的误差,从而可以有效提高CCD测量薄壁梁式挠性器件下摆量的准确度。实验表明,该方法比传统测量方法准确度提高20倍以上。     

多传感器信息融合技术

多传感器信息融合是Ｃ＾３Ｉ系统和电子综合战系统中的关键技术，本文从信息融合分类出发，讨论了单传感器的信息融合决策理论和技术以及多传感器信息融合原理，提出了多传感器信息融合专家系统，着重讨论贝叶斯法用于二元检测的分布式多传感器信息融合的检测方式。     

Coronal mass ejection detection using wavelets,curvelets and ridgelets: Applications for space weather monitoring

Coronal mass ejections (CMEs) are large-scale eruptions of plasma and magnetic field that can produce adverse space weather at Earth and other locations in the Heliosphere. Due to the intrinsic multiscale nature of features in coronagraph images, wavelet and multiscale image processing techniques are well suited to enhancing the visibility of CMEs and suppressing noise. However, wavelets are better suited to identifying point-like features, such as noise or background stars, than to enhancing the visibility of the curved form of a typical CME front. Higher order multiscale techniques, such as ridgelets and curvelets, were therefore explored to characterise the morphology (width, curvature) and kinematics (position, velocity, acceleration) of CMEs. Curvelets in particular were found to be well suited to characterising CME properties in a self-consistent manner. Curvelets are thus likely to be of benefit to autonomous monitoring of CME properties for space weather applications.     

绳索断裂对二维二次太阳翼展开过程影响分析

为识别二维二次太阳翼关键环节和预示其在轨展开故障模式，开展不同位置绳索断裂失效对太阳翼展开的影响程度分析。采用考虑绳索断裂的绳索联动轮力学模型，建立了适应于不同联动轮半径的联动轮受力模型，提出角度触发约束消除方法，解决了太阳翼第2次展开过程连续仿真问题，建立了太阳翼第2次展开动力学方程，分析了不同位置绳索断裂失效对太阳翼各板展开角度、展开构型和其他绳索张力的影响。分析表明，越靠近星体的绳索联动机构失效对太阳翼展开过程的影响越大，其中连接架上绳索联动机构失效可直接导致二维二次太阳翼在轨展开失败。     

平台摇摆对卡尔曼滤波跟踪精度的影响

通过建立目标相对运动坐标系和目标相对运动观测模型,研究了在平台摇摆影响下,跟踪系统观测到的目标运动状态的变化。在分析捷联垂直基准补偿原理的基础上建立了捷联垂直基准平台摇摆角补偿模型,建立的模型结合捷联垂直基准系统的测量能力对其补偿算法进行了理论推导,使模型适用于实际捷联垂直基准系统。通过建立模型以及仿真研究了平台摇摆作用下卡尔曼滤波跟踪精度的变化,指出了摆造成卡尔曼滤波跟踪精度降低甚至离散的主要原因在于模型误差增大。设计仿真实验验证了结论的正确性,为进一步改进跟踪手段提供了理论参考。     

HTPB官能度数学模型建立

为了研究自由基型液体端羟基聚丁二烯预聚物(HTPB)体系官能度分布情况,对其化学合成中自由电子转移情况进行了分析,并通过数学统计的方法对其官能度分布进行理论数值模拟,建立了适用于自由基型HTPB官能度分布的函数关系式,并与GPC所测结果进行对比。结果显示,计算所得函数关系式与测试数据吻合结果较好,数值模拟结果准确性较高;自由基聚合生产的不同批次的HTPB官能度分布存在较大差异,单官能度分子含量可从5%~24%,二官能度分子的含量可从50%~81%;利用数学统计得到的函数关系,可将复杂的HTPB官能度测试转变为简单的分子量分布测试。     

Contamination of short GRBs by giant magnetar flares: Significance of downward revision in distance to SGR 1806–20

We highlight how the downward revision in the distance to the star cluster associated with SGR 1806–20 by Bibby et al. (2008) reconciles the apparent low contamination of BATSE short GRBs by intense flares from extragalactic magnetars without recourse to modifying the frequency of one such flare per 30 years per Milky Way galaxy. We also discuss the variety in progenitor initial masses of magnetars based upon cluster ages, ranging from ∼50 M_⊙ for SGR 1806–20 and AXP CXOU J164710.2–455216 in Westerlund 1 to ∼17 M_⊙ for SGR 1900+14 according to Davies et al. (2009) and presumably also 1E 1841–045 if it originated from one of the massive RSG clusters #2 or #3.     

A fast pulse phase estimation method for X-ray pulsar signals based on epoch folding

X-ray pulsar-based navigation (XPNAV) is an attractive method for autonomous deep-space navigation in the future. The pulse phase estimation is a key task in XPNAV and its accuracy directly determines the navigation accuracy. State-of-the-art pulse phase estimation techniques either suffer from poor estimation accuracy, or involve the maximization of generally non-convex object function, thus resulting in a large computational cost. In this paper, a fast pulse phase estimation method based on epoch folding is presented. The statistical properties of the observed profile obtained through epoch folding are developed. Based on this, we recognize the joint prob-ability distribution of the observed profile as the likelihood function and utilize a fast Fourier transform-based procedure to estimate the pulse phase. Computational complexity of the proposed estimator is analyzed as well. Experimental results show that the proposed estimator significantly outperforms the currently used cross-correlation (CC) and nonlinear least squares (NLS) estima-tors, while significantly reduces the computational complexity compared with NLS and maximum likelihood (ML) estimators.     

A cost driven predictive maintenance policy for structural airframe maintenance

Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance stop.With progress in sensor technology and data processing techniques,structural health monitoring (SHM) systems are increasingly being considered in the aviation industry.SHM systems track the aircraft health state continuously,lead ing to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule.This paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter (EKF) with a first order perturbation (FOP) method.By using the information given by this prognostics method,a novel cost driven predictive maintenance (CDPM) policy is proposed,which ensures the aircraft safety while minimizing the maintenance cost.The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is imple mented.Under the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies:scheduled maintenance and threshold based SHM maintenance.The comparison results show CDPM could lead to significant cost savings.     

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.