WinCC与PLC采集数据间快速交换及显示的研究及应用

针对WinCC和PLC构成的两级计算机控制系统中,WinCC不能实现0.25s以下的实际数据的快速实时采集及显示,以伺服电机驱动的连铸结晶器非正弦振动控制系统为背景,利用S7-400 PLC框架中的FM-458和EXM-438模块对实际数据进行实时采集,并利用WinCC数据归档以及S7-400 PLC的AR SEND功...     

多点快速采集系统中信号可靠转贮技术研究

在直径为10cm的受光面上均匀分布有256个光电探测器,需要将这些探测器所反映的激光能量分布及变化情况的数据即时采集并传送到上位机实时显示。以数据采集和快速传输为目的,介绍了以W77E58为CPU的256点快速采集系统构成及工作原理,讨论了以FT245BM为核心构成的USB接口电路进行实时传送的电路原理及实现过程,较好地解决了对多个监测点实时快速采集和快速传送问题。     

一种IP网络友好的Overlay路由机制*

现有IP网络存在不支持QoS,故障恢复速度慢等问题。作为克服或屏蔽这些缺陷的一种有效手段,Overlay网络在当前Internet上被广泛部署和应用。目前存在很多的Overlay路由结构和方法。然而在现存的多层路由中,上层Overlay网络在路由决策时通常对底层的IP网络性能和状态缺乏有效的协调和感知,致使上层Overlay路由和底层IP路由常常处于非协同、非优化工作状态,产生大量路由抖动和次优路由。为解决这些问题,提出了一种底层IP网络友好的Overlay路由机制,其基本思路为：增加Overlay网络的层感知能力,减少路由抖动增加Overlay路由的稳定性。Overlay网络根据底层IP网络的节点跳数、链路带宽、丢包率等反映底层IP网络性能的信息做出路由决策。实际网络中,通过调整Overlay网络的链路代价有效控制Overlay网络的路由决策。最后仿真结果表明：与传统双重路由（Dual Routing）相比,此IP网络友好Overlay路由机制在减少Overlay网络路由抖动,降低Overlay网络路径代价膨胀,提高Overlay网络故障恢复成功率和满足Overlay业务需求等方面有优势。     

半透膜仪采集空气中多氯联苯采样速度与其结构和性质定量构效关系研究

根据MOPAC2009软件包中PM6算法得到的分子描述符研究半透膜仪(SPMDs)采集大气中多氯联苯(PCBs)采样速度(R_(air))的定量构效关系(QSPR)模型,并分析影响R_(air)的关键因素。以半经验PM6算法得到的分子量子化学描述符作为预测变量,采用偏最小二乘算法(PLS)构建了R_(air)的QSPR模型。根据交叉验证,所得到的最佳模型中PLS成分解释的因变量的累积变异(Q~2_(cum))为0.683,这表明该模型具有良好的预测能力和稳健性。通过外部验证和将实验测得的R_(air)与预测得到的R_(air)进行比较,对所构建模型的稳定性和可靠性进行了验证,结果表明无论是训练组还是预测组,其预测值与实测值间均具有较好的线性关系,线性相关系数均大于0.8376。对PCBs采样速度R_(air)的主要影响因素为PCBs与SPMDs中甘油三油酸酯分子间的相互作用大小和为将PCBs溶解在甘油三油酸酯中形成洞穴所需能量要求。     

能耗最优的水下滑翔机采样路径规划

研究了以能耗为优化准则的水下滑翔机海洋环境参数采样路径规划方法.首先,根据水下滑翔机的运动特点,建立了水下滑翔机采样作业过程的能耗模型;其次,基于能耗模型提出了一种能耗最小的滑翔运动参数优化方法,该方法避免了求解复杂的混合整数非线性规划问题;之后,在能耗最优的滑翔运动参数优化基础上,提出了一种基于两步链式Lin-Ker...     

基于ZOOM-FFT的移频信号参数算法研究

为了准确检测轨道电路移频信号的参数,在分析国内外轨道电路移频信号频谱特点的基础上,提出了针对两种不同信号分别采用整周期和欠采样的采样方法,在以上采样的基础上,介绍了ZOOM-FFT算法的原理和实现步骤,并采用ZOOM-FFT对信号载频附近的频段进行频谱细化放大,提取实验数据。仿真结果表明上述方法是可行的,可以准确检测轨道电路移频信号的参数,有效提高了信号的频率分辨率,满足了技术指标的要求。     

Approaches for scaling DBSCAN algorithm to large spatial databases

The huge amount of information stored in datablases owned by coporations(e.g.retail,financial,telecom) has spurred a tremendous interest in the area of knowledge discovery and data mining.Clustering.in data mining,is a useful technique for discovering intersting data distributions and patterns in the underlying data,and has many application fields,such as statistical data analysis,pattern recognition,image processsing,and other business application,s Although researchers have been working on clustering algorithms for decades,and a lot of algorithms for clustering have been developed,there is still no efficient algorithm for clustering very large databases and high dimensional data,As an outstanding representative of clustering algorithms,DBSCAN algorithm shows good performance in spatial data clustering.However,for large spatial databases,DBSCAN requires large volume of memory supprot and could incur substatial I/O costs because it operates directly on the entrie database,In this paper,several approaches are proposed to scale DBSCAN algorithm to large spatial databases.To begin with,a fast DBSCAN algorithm is developed.which considerably speeeds up the original DBSCAN algorithm,Then a sampling based DBSCAN algorithm,a partitioning-based DBSCAN algorithm,and a parallel DBSCAN algorithm are introduced consecutively.Following that ,based on the above-proposed algorithms,a synthetic algorithm is also given,Finally,some experimental results are given to demonstrate the effectiveness and efficiency of these algorithms.     

基于广义遗传算法的自适应重要抽样理论

1 引言随着计算技术和软件工具的迅猛发展,具有良好普适性的数值模拟方法在许多领域开始受到了广泛的重视。由于Harbitz,Melchers,Wu和本文作者的一系列工作,基于重要抽样理论的非线性系统可靠性分析技术取得了很大的进展。尽管如此,基于重要抽样理论的非线性系统可靠性分析技术中一些带有根本性的理论问题并没有彻底解决。突出表现是,对于广义多设计点问题、寻找所有设计点的求解算法不仅没有提出,甚至没有提出过合理的求解思路。造成这一局面的原因是,多设计点问题的求解需以非连通域非线性系统全局优化问题的解决为前提,而后一问题在     

Adaptive simulation for system reliability analysis of large structures

This article proposes an efficient simulation-based methodology to estimate the system reliability of large structures. The proposed method uses a hybrid approach: first, a probabilistic enumeration technique is used to identify a significant system failure sequence. This provides an initial sampling domain for an adaptive importance sampling procedure. As further simulations are performed, information about other significant sequences is incorporated to refine the sampling domain and to estimate the failure probability of the system. The adaptive sampling overcomes the restrictive assumptions of analytical techniques, yet achieves the robustness and accuracy of basic Monte Carlo simulation in an efficient manner. In this article, the proposed method is implemented using the ANSYS finite element software, and is applied to the system reliability estimation of two redundant structural systems, a six-story building frame and a transmission tower. Both ductile and brittle failure modes are considered. The method is structured in a modular form such that it can be easily applied to different types of problems and commercial software, thus facilitating practical application.     

Filtered Jitter

Jitter is one popular way of generating samples for stochastic sampling in computer graphics. The Poisson disk distribution better approximates that of the human photomosaic. In this paper we examine the spatial and frequency space behaviour of a number of existing algorithms for generating stochastic samples and propose a new algorithm based on low pass filtering a jittered set of displacements. The distribution is at least as much like that of the human photomosaic as any existing algorithm, while being fast to compute.