电站磨煤机齿轮磨损防护技术应用研究

分析了火电厂筒式钢球磨煤机传动齿轮磨损的机理,介绍了堆焊、热喷涂和润滑处理3种磨损防护方法,结合火电厂的实际应用,根据磨损程度的不同,提出端面换向法、等离子喷涂法、堆焊修复法与高级重负荷工业齿轮润滑油润滑处理配合应用,可较好地解决煤机齿轮磨损问题.     

荆州区沙港水库水文自动测报系统集成设计与应用

介绍了沙港水库水文自动测报系统的组织架构设计及系统功能,通过近两年的运维监测管理与效益分析,该系统为水库工程的安全运行和下游太湖港的防洪减灾提供了有力保障,进一步提升了水库水雨工情信息监测与防汛现代化管理水平,最大限度地发挥了水库的综合效益。     

基于数字图像处理的混凝土细观有限元建模

将混凝土看成由水泥砂浆、粗骨料及两者之间的界面组成的三相复合材料。采用MATLAB图像处理工具,选取窗口大小为5×5的像素矩阵对二值图像进行中值滤波处理,然后以结构元素形状为disk、结构半径为2的像素矩阵进行图像形态学处理,最后对图像进行边缘检测以提取二维混凝土骨料边界。基于8连通区域的图像轮廓跟踪算法,运用几何矢量转换技术得到混凝土细观结构图,并在有限元软件ANSYS中对细观数值模型进行了加载试验。结果表明,用该方法得到的细观数值模型与原图像吻合好,可真实地研究混凝土在宏、细观方面的力学性能。     

模糊综合评价法在长江下游贵池河段水质评价中的应用

对水质评价存在诸多方法,而模糊综合评价法具有评价结果合理、更接近客观实际等优点,因而得到越来越广泛的应用。通过模糊评价方法对长江下游贵池河段2005～2009年间水环境综合评价,并采用加权平均原则求取隶属等级,取得较好的效果。     

GMRP组播功能测试

GMRP协议是针对于二层交换机的组播测试协议。通过详细的探讨,可以了解以太网交换机组播技术的实现和使用,组播协议GMRP更深层次的理解,及其在交换机组播测试中的应用。通过GOOSE报文来检测以太网交换机的组播功能。     

大尺寸玻璃网格板制作工艺的研究

玻璃网格板是一种相互垂直的纵、横刻线的二维线纹标准器,用来检测航测仪器、遥感仪器和各类二维坐标测量仪器的精度,因此,它的精度直接影响待检仪器的精度。结合计量圆光栅的制作工艺,详细介绍了基于光刻胶的玻璃网格板新型制作工艺,检验结果表明该种工艺制作的玻璃网格板线条均匀,280mm内刻线间距精度小于1μm。     

Performance of Sewage Sludge Treatment and Electricity Generation by Different Configuration Microbial Fuel Cells

This paper compared the degradation efficiency of sludge organic matters and electric-production by two typical microbial fuel cells——dual-chamber microbial fuel cell(DMFC)and single chamber air cathode microbial fuel cell(SAMFC),and the variations of sludge protein,polysaccharide and ammonia nitrogen within the systems were also investigated.The results showed that the concentration of sludge soluble chemical oxygen demand,protein and carbohydrate of DMFC are higher than these of SAMFC during the systems operation,while DMFC can achieve a better ammonia nitrogen removal than SAMFC.Under the same operation condition,the stable voltage output of DMFC and SAMFC is 0.61 V and 0.37 V;the maximum power density of DMFC and SAMFC is 2.79 W/m3and 1.25 W/m3;TCOD removal efficiency of DMFC and SAMFC is 34.14%and 28.63%for 12 d,respectively.Meanwhile,DMFC has a higher coulomb efficiency than SAMFC,but both are less than5%.The results showed that DMFC present a better performance on sludge degradation and electric-production.     

Application of BP Neural Network in Prediction of Cu-Pb Composite Plates Properties

Abstract： The artificial neural networks（ANN） , which have broad application, are proposed to develop Cu-Pb composite plates materials. Based on the back propagation（BP） algorithm of the forward muhilayer perceptron, the model to predict the shear stress under different ingredient of the third element and the hot dipping temperature for Cu-Pb composite plates are established. Then the relational model among the third element, hot dipping temperature and shear stress by using the limited data are studied, and the forecast average error is 4%. This model can satisfy the requirements of the precision of forecast in the project experiment process. The results show that the corresponding shear stress is greater when the third element in the element contains more Sn; the most appropriate temperature of hot-dip plating about is 340℃, ＇after predicted with lead/the third element/the best performance of copper composite material element of the third group is the one-element Sn, hot dip plating temperature is 335 ℃ ; two-element is 90% Sn 10% Bi, and hot dip plating temperature is 345 ℃. The prediction results can be used for a reference in instructing the further experimental design.     

Eigenvalue Modeling and Cross-Correlation Analysisfor 6.0-6.4 GHz MIMO Channel

In Multiple-Input Multiple-Output （MIMO） system, the number of positive channel matrix eigenvalues ~s directly related to system performance. In order to characterize and model channel matrix eigenvalues, channel measurements at 6. 0 -6. 4GHz by using 4 ~ 4 MIMO structure were conducted in a typical classroom environment. Based on measured data, the eigenvalues were modeled as Log-Normal distributed random variables and parameterized. Furthermore, Cross-Correlation （CC） coefficients of eigenvalues were estimated. The measurement results show that, under both Light-Of-Sight （LOS） and Non- Light-Of-Sight （NLOS） scenarios, eigenvalues are highly de-correlatod so that CC can be ignored for eigenvalue model.