弹性环式挤压油膜阻尼器动力设计方法

弹性环式挤压油膜阻尼器(ERSFD)与传统挤压油膜阻尼器(SFD)相比,在动力特性方面具有一定的特色.以燃气涡轮发动机用ERSFD为对象,基于有限元挤压油膜理论对ERSFD的弹性环支承刚度、油膜压力场分布和油膜阻尼等特性进行了研究.根据ERSFD的结构特点,利用有限元法分析其动力特性不仅具有模型简单、计算量小的优点,而且能考虑到各种复杂的边界条件及封严装置.研究结果表明,本计算方法和结果可以作为ERSFD结构优化的依据.与SFD(Squeeze Film Damper)相比,ERSFD具有分段式油膜间隙,可利用弹性环的弹性变形来调整油膜间隙,将油膜间隙控制在一个合适的范围内,从而有效地避免传统SFD在一定工作条件下的非线性振动现象的发生.      

敏捷导弹气动力/侧向推力复合控制特性分析研究

讨论了敏捷导弹的气动力与姿控发动机侧向推力复合控制.提出将控制系统分成控制律和复合逻辑两部分进行设计的方法,对敏捷导弹进行复合控制,并通过具体的仿真实例比较了在纯气动控制以及姿控发动机在连续和脉冲形式下的控制效果.最后分析了姿控发动机到拦截器质心的距离对控制效果的影响.      

论空间交会最终平移段制导设计

文章阐述了空间交会最终平移段的制导设计方法。在最终平移段 ,追踪航天器沿视线方向作受迫运动 ,逼近目标航天器对接部位 ,追踪航天器相对速度的变化一般考虑指数型与等速型两种模式 ,采用分段制导策略。由追踪航天器相对运动轨迹及速度变化率确定机动加速度 ,在工程上采用多次有限常推力机动方式或多次冲量机动方式     

VLIW上的软件旁路与细粒度并行调度

描述并分析了一种新型的VLIW(Very Long Instruction Word)机器模型,为充分利用该模型的并行特性,提出了基于静态单一赋值(SSA)表示的软件旁路方法,以及集成的基于操作的指令调度与寄存器分配算法.与常规的软件旁路方法和基于周期的调度方法相比,该方法可以灵活地进行结果寄存器的分配,并有效减少由重用结果寄存器导致的"危险值"溢出次数,生成高质量的目标代码.      

一种SAR图像特征增强新方法

军事目标的SAR图像特征在合成孔径雷达目标识别(SAR ATR)中扮演着重要的角色。提出了一种在多小波域中用维纳滤波重构进行SAR目标图像特征增强的新方法,并在此基础上进行了目标图像分割。实验结果表明,该方法能够有效增强SAR图像中的目标区域特征,增大目标和背景杂波之间的统计可分离度,有利于目标图像的精确分割和特征提取。     

Demonstration of the use of the Doppler Orbitography and Radio positioning Integrated by Satellite (DORIS) measurements to validate GPS ionospheric imaging

There is a lack of independent ionospheric data that can be used to validate GPS imaging results at mid latitudes over severe storm times. Doppler Orbitography and Radio positioning Integrated by Satellite (DORIS), a global network of dual-frequency ground to satellite observations, provides this missing data and here is employed as verification to show the accuracy of the ionospheric GPS images in terms of the total electron content (TEC). In this paper, the large-scale ionospheric structures that appeared during the strong geomagnetic storm of 20 November 2003 are reconstructed with a GPS tomographic algorithm, known as MIDAS, and validated with DORIS TEC measurements. The main trough shown in an extreme equatorward position in the ionospheric imaging over mainland Europe is confirmed by DORIS satellite measurements. Throughout the disturbed day, the variations of relative slant TECs between DORIS data and MIDAS results agree quite well, with the average of the mean differences about 2 TECu. We conclude that as a valuable supplement to GPS data, DORIS ionospheric measurements can be used to analyse TEC variations with a relatively high resolution, ∼10 s in time and tens of kilometres in space. This will be very helpful for identification of some highly dynamic structures in the ionosphere found at mid-latitudes, such as the main trough, TID (Travelling Ionospheric Disturbances) and SED (Storm Enhanced Density), and could be used as a valuable auxiliary data source in ionospheric imaging.     

Prospects of using a permanent magnetic end effector to despin and detumble an uncooperative target

Space debris, such as defunct satellites and upper stages of rockets, becomes an uncooperative target after losing its attitude control and communication ability. In addition, tumbling motion can occur due to environmental perturbations and residual angular momentum prior to the object’s end-of-mission. To minimize the collision risk during docking and capturing of the tumbling target, a non-contact method based on the eddy current effect is put forward to transmit the control torque to the tumbling target. The main idea is to induce a controllable torque on the conducting surface of the tumbling target using a rotational magnetic field generated by a Halbach rotor. The radial and axial Halbach rotors are used to damp the spinning and nutation motions of the target, respectively. The normal and tangential force are evaluated concerning the relative pose between the chaser and the target. A simplified dynamic model of the nutation damping and despinning processes is developed and the influences of the asymmetrical principal moments of inertia and transverse angular velocity are discussed. The numerical simulation results show that the designed Halbach rotor stabilized the target attitude within an acceptable time. The electromagnetic nutation damping and despinning method provides new solutions for the development of on-orbit capture technology.     

Ground-Based Cloud Using Exponential Entropy/Exponential Gray Entropy and UPSO

Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast. Thus safety of aircraft taking off and landing and air flight can be guaranteed. Thresholding is a kind of simple and effective method of cloud classification. It can realize automated ground-based cloud detection and cloudage observation. The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect. Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation. In view of the above-mentioned problems, multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization （UPSO） are proposed. Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy. In addition, exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster. Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy. In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection, the UPSO algorithm is adopted. It can find the optimal thresholds quickly and accurately. As a result, the real-time processing of segmentation of groundbased cloud image can be realized. The experimental results show that, in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy, the proposed methods can extract the boundary shape, textures and details feature of cloud more clearly. Therefore, the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.     

Development of a CELSS Experimental Facility

A CELSS Experimental Facility was developed two years ago. It contains a volume of about 40.0 m³ and a cultivating area of about 8.4 m²; its interior atmospheric parameters such as temperature, relative humidity, oxygen concentration, carbon dioxide concentration, total pressure, lighting intensity, photoperiod, water content in the growing-matrix, CO₂-added accumulative amount, O₂-released accumulative amount and ethylene concentration are all controlled and logged automatically and effectively; its growing system consists of two rows of racks along its left-and-right sides separately, each side holds two upper-and-lower layers, and the vertical distance of each growing bed can be adjusted automatically and independently; lighting sources consist of both red (95%) and blue (5%) light-emitting diodes (LED), and the average lighting intensity of each lamp bank at 20-cm distance position under it, reaches to 255.0 μmol m⁻² s⁻¹. After that, demonstrating tests were carried out and were finally followed by growing lettuce in the facility. The results showed that all subsystems operated well and all parameters were controlled automatically and efficiently. The lettuce plants in the system could grow much well. Successful development of this system laid a necessary foundation for future larger-scale studies on CELSS integration technique.     

A novel variable-lag probability hypothesis density smoother for multi-target tracking

It is understood that the forward-backward probability hypothesis density (PHD) smoothing algorithms proposed recently can significantly improve state estimation of targets. However, our analyses in this paper show that they cannot give a good cardinality (i.e., the number of targets) estimate. This is because backward smoothing ignores the effect of temporary track drop- ping caused by forward filtering and/or anomalous smoothing resulted from deaths of targets. To cope with such a problem, a novel PHD smoothing algorithm, called the variable-lag PHD smoother, in which a detection process used to identify whether the filtered cardinality varies within the smooth lag is added before backward smoothing, is developed here. The analytical results show that the proposed smoother can almost eliminate the influences of temporary track dropping and anomalous smoothing, while both the cardinality and the state estimations can significantly be improved. Simulation results on two multi-target tracking scenarios verify the effectiveness of the proposed smoother.