层合复合材料簧片单元弯曲力学性能

为提高空间可展铰链的运行稳定性和可靠性,减轻结构质量,研究了碳纤维增强层合复合材料簧片单元的弯曲性能.以衡量簧片驱动能力的应变能、稳态弯矩以及簧片自锁能力的屈曲临界弯矩为力学性能指标.分析了可折叠自展开的簧片单元在弯曲折叠过程中,复合材料铺层角度、铺层厚度和簧片截面半径对各性能指标的影响.研究结果表明:随着复合材料铺层角度的增加,簧片驱动能力增强,但其自锁能力基本不变;随着复合材料铺层厚度和截面半径的增加,簧片的驱动能力和自锁能力均增强;随着材料铺层角度、截面半径的增加,簧片的横截面出现截面变形现象且伴随微小回弹.研究结果对于空间簧片式铰链驱动性能的改进具有一定的参考价值.     

钢轨表面缺陷图像自适应分割算法

针对钢轨表面缺陷提取时的灰度分布不均与杂散光干扰问题,在背景差分法的基础上提出了一种钢轨表面缺陷图像自适应分割算法.首先,通过统计钢轨图像中各行像素灰度特征,结合其均值与标准差分布曲线快速提取钢轨表面区域;然后,进行区域与边缘特征的均值窗口自适应选取;最后,根据均值模糊原理建立背景图像模型并进行图像差分,实现了钢轨表面缺陷分割.实验结果表明:提出的轨面提取算法快速、有效;钢轨表面缺陷自适应分割算法在凸显图像中缺陷部分的同时,有效减少了光照变化和反射不均的影响.该方法对测试图像的召回率和准确率分别达到了95.4%和81.3%.     

Method to suppress moving targets in SAR images

In the high-resolution wide-swath (HRWS) SAR system, the moving targets are usually smeared and imaged at incorrect positions in the resulting SAR image by utilizing the traditional stationary scene imaging processing. Moreover, these defocused moving targets may cover the stationary scene. The number of spatial degrees of freedom required for suppressing moving targets by the traditional space-time adaptive processing framework is equal to the number of the moving targets in the SAR scene multiplied by the PRF undersampling number. This requirement is hard to meet in practice. In order to overcome the above problem, a new space-time adaptive processing framework based on azimuth Deramp processing is proposed in this paper. Firstly, the moving targets are coarsely focused in the space-time plane through the azimuth Deramp processing. In this case, only one spatial degree of freedom is needed for suppressing one moving target. If there are multiple targets, it can effectively reduce the required degrees of freedom by utilizing the dynamic steering vector concept. Last, simulation results are provided to show the validity of the proposed method.     

Fast sensing method in compressive sensing with low complexity

The random sensing algorithms are hard for hardware implementation while the deterministic sensing algorithms have difficulty in acquiring large signals in the sensing systems of compressive sensing. This paper proposes a fast sensing method for compressive sensing with low complexity. The input signal is firstly permuted by an m-sequence controlled interleaving device. Then the permuted signal is transformed by the fast Walsh-Hadamard transform and down sampled to generate the measurements. Theoretical analysis indicates that the entries of the corresponding sensing matrices are asymptotically normally distributed. Simulation results show that the sensing performance of the corresponding matrices is almost the same as that of completely random sensing operators with a shorter computational time cost. The proposed method has good sensing performance and is easier for hardware implementation, which is meaningful in practice.     

Variable sorting based on fault tree structure adjustment for multi-valued decision diagrams

The dynamic fault tree does not have the ability of fault calculation when analyzing the reliability of the system, so it needs to be modeled and analyzed by means of multi-valued decision diagrams and so on. The dynamic fault tree is translated into a multi-valued decision diagram according to the ordering of variables of basic events which affects the size of the generated multi-valued decision diagram and the cost of traversal to get cut sequences. An adjustment method of the dynamic fault tree structure is proposed based on the importance degree of repeated events, dynamic gates and the locations of events of the dynamic fault tree. By taking the fact that the basic events at the same level are equally important into account, an improved dynamic variable ordering method and ordering generation algorithm for the multi-valued decision diagram are presented in this paper. The result analysis of an example shows that the improved dynamic variable ordering method can reduce the size of the multi-valued decision diagram and space and time complexity of the reliability calculation compared to the similar methods.     

利用测距值优化的室内三维定位算法

为了解决实际误差分布与假设误差分布不匹配导致最小二乘三维定位算法精度较低的问题,提出一种基于测距值优化的最小二乘室内三维定位算法.结合残差修正、Cayley-Menger行列式及空间四面体几何约束,利用非线性规划方法优化测距值,使测距误差符合高斯分布特性,从而提高最小二乘三维定位算法的定位精度.实验对比分析结果显示,所提算法具有较高的定位精度及稳定性.     

基于大学物理教学的参与式教学改革有效实施研究

参与式教学是一种将学生放在教育教学活动的主体位置,教师通过组织、设计活动形式,全面调动学生积极参与、创造性学习与发展的教育理念、教育模式.文章解读了参与式教学模式的内涵,分析了在大学物理中实施参与式教学改革的必要性,讨论了大学物理参与式教学改革的具体实施方法,以寻找适合当前创新型人才培养模式的大学物理的教学方法.     

LYSO∶Ce纳米粉体的溶胶-共沉淀法制备及其发光性能

采用溶胶-共沉淀法,分别以NH_3·H_2O和NH_4HCO_3为沉淀剂,制备了Lu2(1-x-y)Y2xSiO5∶yCe~(3+)(LYSO∶Ce)纳米粉体。采用XRD、SEM和荧光光谱测试手段对样品进行分析,讨论了沉淀剂、煅烧温度、Y~(3+)掺杂比例对粉体晶相的影响,分析了Ce~(3+)含量和Y~(3+)含量对样品发光性能的影响。结果表明,以NH_4HCO_3为沉淀剂,在煅烧温度为1300℃下,Ce~(3+)含量为0.01,Y~(3+)含量为0.05时LYSO∶Ce样品发光性能最好,并且样品的发光强度高于Lu_2SiO_5∶Ce样品,粉体粒度分布均匀、纯度高、分散性好,粒径在100nm~200nm范围。     

YAG:Ce~(3+)荧光粉的制备工艺及发光性能研究

采用高温固相法制备了YAG:Ce~(3+)荧光粉,通过XRD、SEM和荧光光谱等对样品进行了分析。系统地研究了不同种类助熔剂、烧结温度、时间对YAG:Ce~(3+)荧光粉结构、形貌及发光性能的影响。通过调节助熔剂、烧结温度和时间等工艺参数,在不经过破碎、后处理工艺的条件下,制备出了形貌规则、粒度分布均匀、发光性能优良的YAG:Ce~(3+)荧光粉。研究发现在1600℃,保温5个小时,以BaF_2作为助熔剂的条件下,样品的形貌及发光性能均达到最好。     

微博信息流行度预测研究综述

微博的出现改变了传统的信息传播方式。文章针对微博流行度预测的一系列问题展开综述。在对微博流行度预测问题进行定义的基础上, 从微博内容、用户信息和网络结构3方面对影响微博流行度的主要因素进行介绍,对基于时间序列、基于流行病模型、基于分类模型和基于回归模型的4种微博信息预测主流方法进行比较,指出流行度预测未来的研究方向主要集中在时间粒度的划分、最小观测时间的确定、微博流行度的动态预测等方面。该研究对信息检索、舆情研判、企业营销等具有重要意义。