Picosecond laser trimming of ceramic cores with porous multi-scale particle microstructure

The ceramic core, produced by hot injection molding, is one of the critical components for manufacturing high-performance aircraft engine turbine blades. However, the injection molding process will cause defects such as burrs and flashes in the fine structure of the formed ceramic core. Manual trimming is necessary, but the trimming quality is poor, and the yield is low. In this paper, the online trimming method of ceramic cores is studied. Based on the orthogonal experiment method, the optimal laser parameters for processing the ceramic core's porous multi-scale particle structure material were obtained. Further, the problems of the match head and tail phenomenon and dimensional accuracy improvement in trimming ceramic cores have been studied. A path optimisation method is proposed to improve the quality and accuracy of the trimming profile effectively. Finally, the overall process flow of ceramic core trimming is elaborated, and experimental verification is given. The results show that the ceramic core online trimming method proposed in this paper has advantages of high precision and high yield compared with the manual method, which will have substantial potential application value in the aviation field.     

北京谱仪漂移室读出电子学校准电路

本文介绍的电路可同时进行时间和电荷校准,它的校准量程大,精度高,稳定性好,可输出864路指数形校准信号,并可手动或程控。它的时间校准精度优于±250ps,电荷量校准精度优于±1％。     

Introduction of a nonlinearity measure for principal component models

Although principal component analysis (PCA) is an important tool in standard multivariate data analysis, little interest has been devoted to assessing whether the underlying relationship within a given variable set can be described by a linear PCA model or whether nonlinear PCA must be utilized. This paper addresses this deficiency by introducing a nonlinearity measure for principal component models. The measure is based on the following two principles: (i) the range of recorded process operation is divided into smaller regions; and (ii) accuracy bounds are determined for the sum of the discarded eigenvalues. If this sum is within the accuracy bounds for each region, the process is assumed to be linear and vice versa. This procedure is automated through the use of cross-validation. Finally, the paper shows the utility of the new nonlinearity measure using two simulation studies and with data from an industrial melter process.     

Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests

The goal of this research was to compare narrowband hyperspectral Hyperion data with broadband hyperspatial IKONOS data and advanced multispectral Advanced Land Imager (ALI) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data through modeling and classifying complex rainforest vegetation. For this purpose, Hyperion, ALI, IKONOS, and ETM+ data were acquired for southern Cameroon, a region considered to be a representative area for tropical moist evergreen and semi-deciduous forests. Field data, collected in near-real time to coincide with satellite sensor overpass, were used to (1) quantify and model the biomass of tree, shrub, and weed species; and (2) characterize forest land use/land cover (LULC) classes.The study established that even the most advanced broadband sensors (i.e., ETM+, IKONOS, and ALI) had serious limitations in modeling biomass and in classifying forest LULC classes. The broadband models explained only 13-60% of the variability in biomass across primary forests, secondary forests, and fallows. The overall accuracies were between 42% and 51% for classifying nine complex rainforest LULC classes using the broadband data of these sensors. Within individual vegetation types (e.g., primary or secondary forest), the overall accuracies increased slightly, but followed a similar trend. Among the broadband sensors, ALI sensor performed better than the IKONOS and ETM+ sensors.When compared to the three broadband sensors, Hyperion narrowband data produced (1) models that explained 36-83% more of the variability in rainforest biomass, and (2) LULC classifications with 45-52% higher overall accuracies. Twenty-three Hyperion narrowbands that were most sensitive in modeling forest biomass and in classifying forest LULC classes were identified and discussed.     

贯彻食用盐新标准 做好食用盐质量检测

介绍了食用盐新国标制定的指导思想，新标准的特点及所修订的内容，指出为做好食用盐的质量检测要掌握和控制的技术要点，以保证和提高盐质分析结果的准确度，确保食用盐产品质量符合标准要求。     

锥面包络螺旋面上影象法成象点的分布规律及与测量精度的关系

建立了锥面包络螺旋面上影象法成象点的数学模型,证明了锥面包络螺旋面上的影象法成象点具有极高精度的共面性,定量分析了由于成象点不能同时共处于瞄准平面上而引入的原理误差及其表现形式,并且指出螺旋面上影象法成象点所具有的共面性在消除上述原理误差的研究中的重要意义。     

Mining evolving data streams for frequent patterns

A data stream is a potentially uninterrupted flow of data. Mining this flow makes it necessary to cope with uncertainty, as only a part of the stream can be stored. In this paper, we evaluate a statistical technique which biases the estimation of the support of patterns, so as to maximize either the precision or the recall, as chosen by the user, and limit the degradation of the other criterion. Theoretical results show that the technique is not far from the optimum, from the statistical standpoint. Experiments performed tend to demonstrate its potential, as it remains robust even under significant distribution drifts.     

新型动态汽车衡称重系统的设计与实现

针对目前现有动态汽车衡称重误差大等问题，提出了一种新型动态汽车衡称重系统的实现方法，该称重系统在基于Intel x86硬件平台和linux操作系统的基础上设计实现的。同时分析了产生称重误差的根本原因。采用了数字信号处理手段来提高动态汽车衡的称重精度。现场测试数据分析表明，该新型动态汽车衡称重系统技术指标优于国家动态衡标准。     

提高大口径金属主镜面形精度的方法

分析了影响Ｒｉｔｃｈｅｙ－Ｃｈｒｅｉｔｉｅｎ光学系统中金属主反射镜面形精度因素，采用有限元法对立交易的加工过程及其安装进行了模拟，指出提高主镜的面形镜度，既要合理主镜材料的热处理工艺，也要对加工参数进行控制。良好的稳定化处理可以有效地消除材料内部的残余应力，保证主镜尺寸的稳定性。提高加工基准的精度，并采用组合加工镜面，可以大大提高主镜的面形精度，最后，给出了主镜的干涉仪检测结果。     

双目传感器结构优化设计

综合分析了摄象机摆放姿态与双目传器有效视场的关系，同以往简单分析方法不同，文中全面分析了各种情况不同结构参数对传感器精度的影响，介绍了摄象机标定及传感器结构参数获取的方法，实验数据表明，上述分析正确，测量结果令人满意。