基于双CPU的太阳能跟踪系统的研究

从提高太阳能电池板的输出功率出发,提出了基于双CPU控制方式的太阳能跟踪系统。系统采用俯仰-水平双轴控制,以单片机STC12C2052AD为光电控制单元的核心处理器,以混合式步进电机为执行机构,以TMS320F2812为核心控制器件的三相正弦波细分驱动器实现了混合式步进电机的精确定位。实验表明系统运行稳定,具有很高的实用价值。     

运动汽车图像静态视点平滑特征优化仿真

由于运动汽车图像在特征采集过程中,汽车处于高速运动状态,采集的过程无法与汽车完全同步,造成汽车的特征像素分量在高速运动中丢失,产生较大的像素运动噪声,使得汽车图像边缘高频特征因为运动干扰而模糊.传统的平滑过渡方法在对运动汽车图像进行平滑处理时,按照图像中像元灰度值计算突变特性,但受到像素丢失与噪声无法抑制的影响,无法解决运动汽车图像高频分量对图像像元灰度值的干扰问题.提出基于替身运动DR算法的运动汽车图像静态视点平滑过渡方法,用替身像素描述汽车在场景中的运动特征,替身像素在场景中运动并同其它汽车的替身进行交互,采用局部化的车辆模型提高运动汽车场景的逼真度,通过依据替身运动的平滑过渡算法完成归一化线性运动汽车图像静态视点的平滑过渡,解决了运动汽车图像的平滑过渡问题.实验结果说明,所提方法可确保运动汽车图像边缘锐化,有效处理平滑噪声和锐化边缘.     

Effects of silicone oil and polymeric modifiers on the mechanical properties of highly filled LLDPE

The effects of coupling agents, silicone oil, and three types of polymeric modifiers on the mechanical properties of linear low density polyethylene (LLDPE) composites highly filled with aluminium hydroxide [Al(OH)₃] were studied. Polymeric modifiers that contain polar groups, such as silane‐grafted polyethylene (Si‐g‐PE) and acrylic‐acid‐grafted ethylene‐vinyl acetate copolymer (AA‐g‐EVA), improve the mechanical properties dramatically, while nonpolar modifiers improve them to some extent. When Al(OH)₃ was treated using a titanate coupling agent, the silicone oil increased the impact strength and elongation at break of the LLDPE/Al(OH)₃ composites. Introduction of a polymeric modifier containing polar groups destroys the beneficial effects of silicone oil on film mechanical properties, while the introduction of a nonpolar elastomeric polymeric modifier retains the high impact strength and elongation at break. SEM analyses provide the indirect evidence of the encapsulation of silicone oil around the filler. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 83: 121–128, 2002     

Rn 上的线性局部保控映射

设φ：Rn →Rn 是一个线性映射,对任意x∈Rn ,都存在与x有关的线性保控映射ψx ,使得φ（x）＝ψx（x）,则称φ是欧氏空间上的一个线性局部保控映射。线性保控映射是线性局部保控映射,其逆命题不成立。文中定义了两个与φ相关的Rn的子集Iφ和IIφ,如果任意Rn上的点都属于Iφ（或IIφ）,那么这个线性局部保控映射φ是线性保控映射。     

Temperature stability and fracture toughness of Nd-Fe-B magnets

Temperature stability and toughness of magnets are very important properties especially for application in motor. In this paper, it is found that temperature stability and toughness of magnets are improved when Fe is substituted with Co andheavy rare earth is substituted for Nd in part and suitable rich B grain-boundary phase is added. In addition, heavy rare earth substitution decreases the remanence temperature coefficient greatly, but has a little effect on Curie temperature of the magnets, which is beneficial to Nd-Fe-B magnets for the application in motor.     

多孔薄壁扁管连续挤压模的研制

介绍了连续挤压模的生产工艺过程 ,模具主要结构及设计参数 ,分析了生产中存在的问题以及采取的措施 ,充分发挥了连续挤压设备的潜力 ,扩大了产品品种     

谈谈水泥土挡墙的合理计算

阐述了水泥土挡墙在工程基坑支护中的作用,并结合工程实例,对水泥土挡墙的合理计算模型进行了探讨。     

Dual–primal proximal point algorithms for extended convex programming

This paper presents a class of dual–primal proximal point algorithms (PPAs) for extended convex programming with linear constraints. By choosing appropriate proximal regularization matrices, the application of the general PPA to the equivalent variational inequality of the extended convex programming with linear constraints can result in easy proximal subproblems. In theory, the sequence generated by the general PPA may fail to converge since the proximal regularization matrix is asymmetric sometimes. So we construct descent directions derived from the solution obtained by the general PPA. Different step lengths and descent directions are chosen with the negligible additional computational load. The global convergence of the new algorithms is proved easily based on the fact that the sequences generated are Fejér monotone. Furthermore, we provide a simple proof for the O(1/t) convergence rate of these algorithms.     

一种相控阵天线安装精度检测与校准

文中论述了一种相控阵雷达天线安装后的精度检测方法。按照雷达天线安装后的几何形态,采用光学测量仪器进行相关的数据采集,建立检测的数学模型,利用线性回归法以及最小二乘法进行数据拟合,计算出安装后雷达天线底面与水平面的最大夹角和天线边缘与正北方向的夹角,并进行了试验误差评估和分析,依据检测数据对雷达天线的水平和方位角度进行校...     

Locally linear discriminant embedding: An efficient method for face recognition

In this paper an efficient feature extraction method named as locally linear discriminant embedding (LLDE) is proposed for face recognition. It is well known that a point can be linearly reconstructed by its neighbors and the reconstruction weights are under the sum-to-one constraint in the classical locally linear embedding (LLE). So the constrained weights obey an important symmetry: for any particular data point, they are invariant to rotations, rescalings and translations. The latter two are introduced to the proposed method to strengthen the classification ability of the original LLE. The data with different class labels are translated by the corresponding vectors and those belonging to the same class are translated by the same vector. In order to cluster the data with the same label closer, they are also rescaled to some extent. So after translation and rescaling, the discriminability of the data will be improved significantly. The proposed method is compared with some related feature extraction methods such as maximum margin criterion (MMC), as well as other supervised manifold learning-based approaches, for example ensemble unified LLE and linear discriminant analysis (En-ULLELDA), locally linear discriminant analysis (LLDA). Experimental results on Yale and CMU PIE face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.