直接磁场定向控制在主变流器中的应用

由于直接磁场定向控制是通过对电机的反馈测量而计算出用于控制算法的定子或转子磁链,具有对电机参数变化的自适应作用,因而更加适合于对控制性能要求较高的主变流器的应用.结合电机的电流模型对转子磁链进行辨识,在控制策略中设计了转速、电流、磁链等多个闭环,采用了简单实用的偏差电压解耦方式,构建了完整的控制方案.通过在150 kVA机组上的各种试验,结果表明该控制系统运行稳定、动态性能好,满足实际运用的要求.     

感应电机转子磁链闭环鲁棒观测方法研究

为了使感应电机在其转速大幅度变化、转子和定子的电阻发生变化及外界干扰等因素影响下获得精确的转子磁链,实现调速系统的高性能以及机车牵引的稳定运行,笔者将感应电机的转速、转子电阻和定子电阻作为调速系统的时变参数,采用线性变参数多胞输出反馈控制器设计理论,提出一种新的转子磁链观测方法;利用现代鲁棒控制理论,通过求解一组线性矩阵不等式组,设计出转子磁链观测器;构建一个基于DSP的物理实验系统,验证了所设计观测器的有效性和先进性,表明系统具有鲁棒H∞性能和良好的动态特性.     

双线超高大跨度浅埋铁路隧道施工技术

结合浙赣铁路罗家里隧道的施工经验,详细介绍了双侧壁导坑法在双线超高大跨浅埋隧道中的应用。通过双侧壁导坑施工方法减小了隧道一次性开挖断面,并结合围岩变形的量测结果,加强支护措施,有效地解决了软弱地层条件下隧道围岩竖、侧向应力过大的难题,保证了施工安全,满足了工期要求。     

直线电机轨道工程GJ-Ⅲ型减振降噪扣件的应用

直线电机系统在城市轨道交通系统有着独特的优势,该系统中减振降噪技术的应用仍然是一个在不断探索和延伸的课题。广州地铁5号线直线电机轨道工程中首次采用我国自行研究生产的减振降噪扣件—G JⅢ型减振降噪扣件,即双层非线型减振降噪扣件,介绍G JⅢ型减振降噪扣件的施工技术应用。     

Local Tensile Strength of Connection Between H-Steel Beam Flange and Concrete-Filled Circular Column Tube with Through Diaphragm

This paper focused on investigating local tensile strength of connection between steel beam flange and concrete-filled circular column tube with through diaphragm. Three specimens were designed and tested to failure,and the structure behavior was studied by experiment and FEM analysis. On the basis of the results obtained, an estimation for local plastic and ultimate strengths of the connections using yield line theory was attempted, which results in a good prediction.     

运输网络最优价格组合研究

铁路客运各区段相互嵌套、衔接，构成运输网络问题．使得寻求其中各区段票价组合成为一个较为复杂的问题．针对多级离散价格，在综合考虑运行区段各级票价对整个网络收益的影响的基础上，定义隐藏价格等概念，将原适用于同质产品的最大凹向包络理论拓展于运输网络领域，引入的最优票价组合方法，为动态定价中各级票价的产生提供理论依据。     

μC/OS-II在ARM处理器上移植过程中的中断处理

讨论了μC/OS-II在ARM7上移植过程中中断处理需要注意的几个问题,介绍了通用中断处理的过程和一般方法,并给出了在基于ARM7内核的LPC2000系列芯片上移植μC/OS-II部分代码。     

用改良的荧光探针法测定外周血淋巴细胞膜流动性及其临床应用

用改良的荧光探针法测定外周血淋巴细胞膜流动性，此方法不需分离细胞膜，操作简便，灵敏度高，批内变异系数CV为0．9％。采用该方法对41例心力衰竭患者及20例正常人外周淋巴细胞膜流动性进行了测定，结果显示：心力衰竭患者外周淋巴细胞膜流动性P值为0．345±0．021，正常人为0．259±0．019，二者有显著差异（P＜0．05）；且发现外周淋巴细胞膜流动性改变与红细胞的改变一致，相关分析表明二者呈正相关（r=0．937，P＜0．05）。     

EXPRESSION OF MATRIX METALLOPROTEINASE-2 AND VASCULAR ENDOTHELIAL GROWTH FACTOR IN HUMAN GLIOMA AND THEIR RELATION TO THE INVASION OF THE TUMOR

Neovascularizationcanbeobservedinthe courseoftumorformationandmalignantinvasion,whichwillpromotethemalignantinvasionofthe tumor[1].Vascularendothelialgrowthfactor(VEGF)andmatrixmetalloproteinases(MMPs)are theimportantadjustiveproteinsintheinvasionand neov…     

Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data

Global Positioning System (GPS) technologies have been increasingly considered as an alternative to traditional travel survey methods to collect activity-travel data. Algorithms applied to extract activity-travel patterns vary from informal ad-hoc decision rules to advanced machine learning methods and have different accuracy. This paper systematically compares the relative performance of different algorithms for the detection of transportation modes and activity episodes. In particular, naive Bayesian, Bayesian network, logistic regression, multilayer perceptron, support vector machine, decision table, and C4.5 algorithms are selected and compared for the same data according to their overall error rates and hit ratios. Results show that the Bayesian network has a better performance than the other algorithms in terms of the percentage correctly identified instances and Kappa values for both the training data and test data, in the sense that the Bayesian network is relatively efficient and generalizable in the context of GPS data imputation.