应用六西格玛提高钛合金超塑成形/扩散连接产品合格率

应用六西格玛提供的质量改进方法和统计分析工具,按照界定、测量、分析、改进、控制的步骤,运用Pareto图、因果图、过程能力分析、多元回归分析等多种工具,深入分析钛合金超塑成形/扩散连接产品制造过程中产生缺陷的根本原因并采取改进措施,有效提高了制造过程能力和产品合格率。     

基于AMESim的某型客机舵面液压系统仿真分析

当某型客机飞控舵面作为液压能源系统的用户时,应用AMESim仿真软件,在相应的载荷作用下,对液压系统所需压力、流量以及相关液压附件参数的设置进行分析,并对舵面的仿真运动结果进行动画演示。     

重量的一种遥测式监测系统

本文提出一种重量信号的无线传输和测量方法。重量信号经传感顺转换成电信号，再经Ｖ／Ｆ变换后调频发射，接收信号解调后单片机处理。单片机的信号处理采用电子计数器测频方法，经过计算送显示单元，实现重量信号的遥测。     

Beam-Park-Experiment-1/2000 with TIRA

A monostatic 24-h debris observation campaign (BPE-1/2000) has been prepared and conducted using FGAN's TIRA L-Band system. Based on experiences from previous Beam-park experiments a similar largely automated data processing is applied on an extended range window of 300–2000km. More than 1500 detections are encountered, 471 of them are verified as being real objects in Low-Earth-Orbit (LEO). PROOF's observation forecasting of catalogued objects is evaluated against the observed objects, and the difficulties obtaining radar cross-sections (RCSs) and object sizes from Beam-park experiments are discussed. Sidelobe detections are identified by using background information like two-line element (TLE) sets and/or catalogued RCSs.In comparison with previous experiments, the statistics show similarities confirming the concept of Beam-park experiments for space debris observations, despite the snapshot character of 24-h experiments. The comparison with MASTER/PROOF'99 and ORDEM2000 leads to a reasonable agreement between models and observations.     

Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots. This type of work will be quite helpful in the near future to develop a hotspots monitoring system using these operational satellites data.     

飞机电气系统参数测试标准实施中问题分析

结合本标准宣贯、研讨会上所提供的信息,分析了飞机电气系统参数测试标准在实际应用中存在的一些问题,并对瞬态电压和频率调制率等重点问题进行了详细的讨论和分析.     

The effect of geocenter motion on Jason-2 orbits and the mean sea level

We compute a series of Jason-2 GPS and SLR/DORIS-based orbits using ITRF2005 and the std0905 standards ( Lemoine et al., 2010). Our GPS and SLR/DORIS orbit data sets span a period of 2 years from cycle 3 (July 2008) to cycle 74 (July 2010). We extract the Jason-2 orbit frame translational parameters per cycle by the means of a Helmert transformation between a set of reference orbits and a set of test orbits. We compare the annual terms of these time-series to the annual terms of two different geocenter motion models where biases and trends have been removed. Subsequently, we include the annual terms of the modeled geocenter motion as a degree-1 loading displacement correction to the GPS and SLR/DORIS tracking network of the POD process. Although the annual geocenter motion correction would reflect a stationary signal in time, under ideal conditions, the whole geocenter motion is a non-stationary process that includes secular trends. Our results suggest that our GSFC Jason-2 GPS-based orbits are closely tied to the center of mass (CM) of the Earth consistent with our current force modeling, whereas GSFC’s SLR/DORIS-based orbits are tied to the origin of ITRF2005, which is the center of figure (CF) for sub-secular scales. We quantify the GPS and SLR/DORIS orbit centering and how this impacts the orbit radial error over the globe, which is assimilated into mean sea level (MSL) error, from the omission of the annual term of the geocenter correction. We find that for the SLR/DORIS std0905 orbits, currently used by the oceanographic community, only the negligence of the annual term of the geocenter motion correction results in a – 4.67 ± 3.40 mm error in the Z-component of the orbit frame which creates 1.06 ± 2.66 mm of systematic error in the MSL estimates, mainly due to the uneven distribution of the oceans between the North and South hemisphere.     

Hypothesis-test-based landcover change detection using multi-temporal satellite images – A comparative study

Remote sensing images and technologies have been widely applied to environmental monitoring, in particular landuse/landcover classification and change detection. However, the uncertainties involved in such applications have not been fully addressed. In this paper two hypothesis-test-based change detection methods, namely the bivariate joint distribution method and the conditional distribution method, are proposed to tackle the uncertainties in change detection by making decisions based on the desired level of significance. Both methods require a data set of class-dependent no-change pixels to form the basis for class-dependent hypothesis test. Using an exemplar study area in central Taiwan, performance of the proposed methods are shown to be significantly superior to two other commonly applied methods (the post-classification comparison and the image differencing methods) in terms of the overall change detection accuracies. The conditional distribution method takes into consideration the correlation between digital numbers of the pre- and post-images and the effect of the known pre-image digital number on the range of the post-image digital number, and therefore yields the highest change detection accuracy. It is also demonstrated that the class-dependent change detection is crucial for accurate landuse/landcover change detection.     

中间件技术的研究及应用

本文在分析了分布式应用系统体系结构发展变化的基础上．阐述了中间件的概念、功能和在可重用、多异构数据源应用系统的作用，对ODBC、BDE／IDAPIT、0LEDB／ADO和JDBC等分布式数据库中间件；CGI、lSAPI／NSAPI、ASP、JSP等中间件进行了分析比较，并给出了中间件技术在教务管理信息系统的应用实例。