相位校正器粘接局部应力控制技术

通过理论分析,对相位校正器的镜面与支撑结构间的粘接建立模型进行仿真研究,提出了在相位校正器镜片上加工小圆柱,使其粘接应力由镜片本身转移到突出部位的小柱子上,有效改善了相位校正器镜面局部粘接应力,使镜面局部高阶像差得到缓解,并通过试验验证了其有效性。     

一种新型彩色三维光学成像系统

提出一种新型三维彩色光学数字成像系统。此系统利用投影结构光对现实世界中的物体进行数字化，同时得到对应的彩色纹理。详细介绍了系统的硬件设计和软件体系结构设计，得到物体彩色纹理的两种不同方法；直接获取和从编码条纹中提取，给出了用该系统得到的实验结果并简单评价了系统的性能。此系统在反求工程、影视制作、三维游戏制作、医学应用等方面有远大的应用前景。     

甲基紫掺杂聚乙烯醇薄膜材料红光多重全息存储

甲基紫掺杂聚乙烯醇薄膜材料在两束相干光照射下生成相位光栅.当改变一束相干光光程,通过监测相位光栅的一级衍射信号强度的变化,可以检测相位光栅的生长和擦除过程.在此实验基础上,讨论了甲基紫掺杂聚乙烯醇薄膜材料多重全息存储的原理与结果.     

大口径宽视场双波段扫描红外相机光学设计

通过分析计算,设计了一种大口径宽视场折射式红外相机光学系统。该系统设计用于超长线阵扫描红外相机的地面演示成像,它能同时对短波2μm—3μm、中波3μm—4.5μm双波段成像,且同时具有24°的大视场和150mm的宽口径,成像质量接近衍射极限。该系统在航天遥感领域应用广泛。     

Ultrasound imaging and evaluation of lesion induced by High Intensity Focused Ultrasound

The present study was to investigate the differential imaging method for detecting HIFU (High Intensity Focused Ultrasound)-induced lesions and the estimation of variation of attenuation for lesion evaluation with log spectral difference algorithm. Experiment results of bovine muscle and liver in vitro were acquired. Several algorithms for lesion detection - Absolute Difference (AD), Sum Absolute Differences (SAD) and Sum Squared Differences (SSD) - were analyzed with several window sizes and threshold values. Then three attenuation parameters were compared to evaluate the degree of tissue damage. It was found that variation of the mean attenuation △α was an effective parameter to evaluate lesions.     

究竟能成多少人像？

处于互成角度的两平面镜角平分线上的点光源在两镜中能成多少个像?笔者经过思考与推证，得出了结论，供同学们参考。     

BEPCII直线加速器相控系统设计研究

为了补偿由于各种因素引起的微波相位漂移,BEPCII直线加速器需要建立微波相位反馈控制系统.能量最大法将用来确定每台功率源的最佳相位.沿直线加速器速调管长廊铺设相位稳定同轴线提供相位参考.现在已经完成了关键部件,如PAD单元、IfA 单元的开发.搭建了相控最小系统对系统进行了验证.     

光纤光栅选频掺Yb3+双包层光纤激光器

利用相位掩模法 ,在D形内包层掺Yb3 双包层光纤一端直接写制出Bragg光栅 ,用作双包层光纤激光器的输出腔镜 .试验得到了线宽为 0 196nm ,波长为 10 5 8 2nm ,最高输出功率为 5 70mW的稳定激光输出 ,解决了激光器中模式竞争造成的输出不稳定现象 .从速率方程出发 ,对激光器的输出功率与抽运功率、光栅反射率的关系以及最佳光纤长度进行了理论分析 ,结果与实验符合很好     

Local Prediction of Chaotic Time Series Based on Support Vector Machine

Based on phase space delay-coordinate reconstruction of a chaotic dynamics system, we propose a local prediction of chaotic time series using a support vector machine （SVM） to overcome the shortcomings of traditional local prediction methods. The simulation results show that the performance of this proposed predictor for making onestep and multi-step prediction is superior to that of the traditional local linear prediction method and global SVM method. In addition, it is significant that its prediction performance is insensitive to the selection of embedding dimension and the number of nearest neighbours, so the satisfying results can be achieved even if we do not know the optimal embedding dimension and how to select the number of nearest neighbours.