Synthesis of nanophase tungsten carbide by electrical discharge machining

Tungsten carbide nanopowders were synthesized successfully by electric discharge machining followed by annealing under a nitrogen atmosphere. The tungsten workpieces were initially melted and evaporated on the working surface during the electric discharge machining process, and then the tungsten powders were reacted with the carbon electrode and the working medium of kerosene to form the nanocrystalline WC_1−x powders. The powders produced were characterized by XRD, SEM, and TEM. When annealing the powders under an N₂ atmosphere, the cubic phases of WC_1−x gradually changed to hexagonal W₂C and then were transformed fully to nanocrystalline hexagonal WC at 1200 °C, with the nanocrystalline tungsten carbide encapsulated in a carbon shell. On the other hand, under an H₂ atmosphere, the WC_1−x phase changed via a W₂C phase to reduced powders of pure tungsten at 1000 °C or were reduced directly from WC_1−x to elemental W.     

Pore‐free mold‐pattern‐transfer method for barrier ribs of HD PDPs

Abstract— Among various barrier‐rib manufacturing processes, the mold‐pattern‐transfer method has potential to reduce processing cost as well as the manufacture of high‐resolution pixels. In this study, the effects of major processing variables of the mold‐pattern‐transfer process on the formation of air‐trapped pores within barrier ribs were examined. The results indicated that with an optimum combination of the processing variables, barrier ribs without trapped defects can be produced, demonstrating the possibility of reducing the number of processing steps and costs of barrier ribs.     

岩石液压致裂中几个问题的研究

论证了流体压力变化与岩石强度变化之间的关系，阐述了流体保持与释放的应力条件和构造环境，总结了两种围岩下的液压致裂模型及其流量方程。     

小型腔式微波离子源的研制

研制了１种用在离子束细胞刻蚀装置中的小型腔式微波离子源，它由石英放电管、同轴谐振腔和封装在管一端的二电极引出系统组成。该源由同轴腔激发起的表面波在石英管内产生等离子体柱。为了提高柱末端等离子体离子引出流密度，选用了在内径７．０ｍｍ直管的一端加上一内径５．０ｍｍ衬管的放电管。在微波频率为２．４５ＧＨｚ，输入功率为９３Ｗ下，氮的引出流密度分别为４８．４ｍＡ／ｃｍ２和９１．７ｍＡ／ｃｍ２。这种表面波放电等离子体源体积小、结构简单，可在较宽的压强范围内产生重复性好、工作稳定的等离子体柱。     

双层辉光离子渗镀钽

介绍了一种新型离子渗镀钽的工艺方法。较好解决了渗镀钽时供给活性钽粒子的总是比方法工艺简单，操作方便，效率高。为充分利用和节约使用昂贵的钽探索了一条实用可行的途径。     

Tree-based partitioning of date for association rule mining

The most computationally demanding aspect of Association Rule Mining is the identification and counting of support of the frequent sets of items that occur together sufficiently often to be the basis of potentially interesting rules. The task increases in difficulty with the scale of the data and also with its density. The greatest challenge is posed by data that is too large to be contained in primary memory, especially when high data density and/or low support thresholds give rise to very large numbers of candidates that must be counted. In this paper, we consider strategies for partitioning the data to deal effectively with such cases. We describe a partitioning approach which organises the data into tree structures that can be processed independently. We present experimental results that show the method scales well for increasing dimensions of data and performs significantly better than alternatives, especially when dealing with dense data and low support thresholds. Shakil Ahmed received a first class BSc (Hons) degree from Dhaka University, Bangladesh, in 1990; and an MSc (first class), also Dhaka University, in 1992. He received his PhD from The University of Liverpool, UK, in 2005. From 2000 onwards he is a member of the Data Mining Group at the Department of Computer Science of the University of Liverpool, UK. His research interests include data mining, Association Rule Mining and pattern recognition. Frans Coenen has been working in the field of Data Mining for many years and has written widely on the subject. He received his PhD from Liverpool Polytechnic in 1989, after which he took up a post as a RA within the Department of Computer Science at the University of Liverpool. In 1997, he took up a lecturing post within the same department. His current Data Mining research interests include Association rule Mining, Classification algorithms and text mining. He is on the programme committee for ICDM'05 and was the chair for the UK KDD symposium (UKKDD'05). Paul Leng is professor of e-Learning at the University of Liverpool and director of the e-Learning Unit, which is responsible for overseeing the University's online degree programmes, leading to degrees of MSc in IT and MBA. Along with e-Learning, his main research interests are in Data Mining, especially in methods of discovering Association Rules. In collaboration with Frans Coenen, he has developed efficient new algorithms for finding frequent sets and is exploring applications in text mining and classification.     

中置式高压电容器柜改进设计

分析了南屯煤矿白马河风井变电所高压电容器柜原设计方案存在的问题,并对其进行了改进设计:选用适用于容性负载的真空断路器;添加放电线圈,并将放电线圈与电容器直接并联,使放电线圈与电容器组成一个完整的放电回路;添加接地开关,接地开关既有机械闭锁又有电气联锁,操作方便,安全性高。实际应用表明,改进设计后的高压电容器柜功能更加完善,更加安全、可靠。     

Characterization of acoustic signals due to surface discharges on H.V. glass insulators using wavelet radial basis function neural networks

A hybrid model incorporating wavelet and radial basis function neural network is presented which is used to detect, identify and characterize the acoustic signals due to surface discharge activity and hence differentiate abnormal operating conditions from the normal ones. The tests were carried out on cleaned and polluted high voltage glass insulators by using surface tracking and erosion test procedure of international electrotechnical commission 60587. A laboratory experiment was conducted by preparing the prototypes of the discharges. This study suggests a feature extraction and classification algorithm for surface discharge classification, which when combined together reduced the dimensionality of the feature space to a manageable dimension, by “marrying” the wavelet to radial basis function neural network very high levels of classification are achieved. Wavelet signal treatment toolbox is used to recover the surface discharge acoustic signals by eliminating the noisy portion and to reduce the dimension of the feature input vector. A radial basis function neural network classifier was used to classify the surface discharge and assess the suitability of this feature vector in classification. This learning method is proved to be effective by applying the wavelet radial basis function neural network in the classification of surface discharge fault data set. The test results show that the proposed approach is efficient and reliable.     

基于偏微分的图像放大算法研究

在研究图片放大算法中,分析了现有的运用偏微分算法在图像法大中的不足,利用图像放大过程中的边缘信息可预知性,本文提出一种新的基于偏微分方程的图像放大算法,这种算法通过将图像边缘检测、平滑处理,然后采用三次样条插值算法对边缘进行相应倍数的放大,并通过对可能出现的锯齿边缘进行细化处理;将处理过的边缘作为放大图像的边缘,从而可以将源图像的边缘很好的保持下来,避免了偏微分方程放大过程中出现的边缘模糊现象。实验结果显示,该方法是一种能够很好的保存图像的边缘信息的图像放大算法。     

Chemical composition and bond structure of carbon-nitride films deposited by CH4/N2 dielectric barrier discharge

Carbon nitride films have been deposited by dielectric barrier discharge with a CH₄/N₂ gas mixture at different conditions. Fourier Transform Infrared (FTIR) spectroscopy, X-ray photo electron spectroscopy (XPS), Raman spectroscopy, Atomic force microscopy (AFM) and ellipsometry were used to systematically study chemical composition, bond structure and surface morphology of deposited films. Various bonds between carbon, nitrogen, hydrogen, and also oxygen were observed.