通化西昌斜拉桥新型单索面牵索挂篮的结构构思、设计及应用

介绍通化西昌斜拉桥单索面牵索挂篮设计原理、构造特点、关键工艺。     

自适应指数平滑模型预测区域经济研究

三次指数平滑法预测区域经济时，平滑参数为一常量，这与实际不符，容易使预测结果误差偏大，甚至严重失真。本文在深入剖析指数平滑模型缺陷的基础上，对其进行改进，建立了自适应指数平滑模型。实践证明，该模型能够更好地反映区域经济发展的动态特性，提高预测的精度。     

随机响应约束下的桁架结构拓扑优化

研究随机响应约束下的桁架结构拓扑优化问题具有重要的工程应用前景.文章采用自适应遗传算法(AGA)求解了随机响应约束下的桁架结构拓扑优化问题.通过引入海明距离生成高质量的初始种群、采用自适应的交叉和变异算子以及对适应度函数进行线性标定这三个步骤改进了遗传算法的搜索效率以及收敛性.在拓扑优化列式中考虑杆件以及各自由度的拓扑变量以精确地模拟优化过程中杆件和结点的删除.建立了随机载荷作用下结构均方响应的表达式,并以此作为拓扑优化问题的约束条件.另外,提出了一些启发式算法来引导杆件和结点的删除.最后,通过对随机激励下的二维桁架以及三维桁架进行拓扑优化计算,证明了本文方法的实用性和有效性.     

基于自适应信息遗传算法的路面模量反算研究

针对在模量反算中,目标函数在最优值附近表现为大片狭长平坦区域的特点,提出了一类反算新算法——自适应信息遗传算法,新算法的优点是根据信息量大小来进行自适应细分模量解空间,从而节约大量的计算时间.改进了实数交叉算子,使用了新的探险策略,从而加强了新算法后期的局部搜索能力.随后的工程实例表明,这种新机制、新策略的引入,能够在...     

无速度传感器感应电机自适应观测器的稳定性分析与设计

分析了感应电机低速发电工况下现有采用极点配置的自适应观测器存在不稳定区域的原因,得出了自适应观测器在全速范围内稳定的条件.在此基础上提出一种改进的速度自适应律和观测器增益矩阵选取方案.应用Lyapunov稳定性理论,得到基于自适应观测器的速度辨识自适应律;观测器的增益矩阵通过求解2 个双线性矩阵不等式得到.在MATLAB/SIMULINK环境下,对基于自适应观测器的无速度传感器感应电机直接转矩控制进行了仿真.仿真结果表明,本文给出的自适应观测器在全速范围内具有良好的稳态和动态性能,并具有很好的鲁棒性.     

基于单板受力的预应力混凝土空心板桥承载力评定

为了研究处于“单板受力”状态桥梁的承载能力,采用已使用10 a的旧桥预应力混凝土空心板的试验数据,对既有空心板桥的承载力状况进行了评定.分别基于荷载横向分布和单板受力模式进行抗力-荷载效应分析,以确定既有桥梁的承载力.结果表明,“单板受力”削弱了上部结构的整体作用,降低了桥梁的整体承载力,使得上部主要承重构件处于非常不利的受力状态,降低了结构的耐久性和安全性.用现有承载力评定方法对处于“单板受力”状态的桥梁进行承载力评定,为既有不利状态的空心板桥的承载力评估提供很大的参考价值.     

基于 CS5464电能计量芯片的研究与应用

介绍了单相电能计量芯片CS5464,描述了其工作原理与软硬件设计,利用低功耗单片机C8051 F330实现对电压、电流等参数的精确测量。     

独塔斜拉桥抗震分析及其合理约束体系研究

以石河子独塔斜拉桥为工程背景,建立有限元抗震模型,采用反应谱法及非线性动力时程分析方法对该桥进行抗震分析,并将二者的结果进行对比。采用三角级数人工合成法生成人工地震波,计算结果与反应谱法基本接近。为研究纵向约束体系对独塔斜拉桥抗震性能的影响,分别对于刚构体系、漂浮体系、竖向支承体系、竖向支承加弹性索体系和竖向支承加黏滞阻尼器（FVD）体系等不同纵向约束体系独塔斜拉桥在罕遇地震作用下进行抗震计算。研究结果表明：当采用活动支座作为竖向支承时,支座摩阻力对结构的抗震性能有较大的提升,计算时应考虑其影响;竖向支承加FVD体系是相对最优的纵向抗震约束体系。     

A bintree energy approach for colour image segmentation using adaptive channel selection

A new hierarchical approach called bintree energy segmentation was presented for color image segmentation. The image features are extracted by adaptive clustering on multi-channel data at each level and used as the criteria to dynamically select the best chromatic channel, where the segmentation is carried out. In this approach, an extended direct energy computation method based on the Chan-Vese model was proposed to segment the selected channel, and the segmentation outputs are then fused with other channels into new images, from which a new channel with better features is selected for the second round segmentation. This procedure is repeated until the preset condition is met. Finally, a binary segmentation tree is formed, in which each leaf represents a class of objects with a distinctive color. To facilitate the data organization, image background is employed in segmentation and channels fusion. The bintree energy segmentation exploits color information involved in all channels data and tries to optimize the global segmentation result by choosing the ＂best＂ channel for segmentation at each level. The experiments show that the method is effective in speed, accuracy and flexibility.     

Connected variable speed limits control and car-following control with vehicle-infrastructure communication to resolve stop-and-go waves

The vision of intelligent vehicles traveling in road networks has prompted numerous concepts to control future traffic flow, one of which is the in-vehicle actuation of traffic control commands. The key of this concept is using intelligent vehicles as actuators for traffic control systems. Under this concept, we design and test a control system that connects a traffic controller with in-vehicle controllers via vehicle-to-infrastructure communication. The link-level traffic controller regulates traffic speeds through variable speed limits (VSL) gantries to resolve stop-and-go waves, while intelligent vehicles control accelerations through vehicle propulsion and brake systems to optimize their local situations. It is assumed that each intelligent vehicle receives VSL commands from the traffic controller and uses them as variable parameters for the local vehicle controller. Feasibility and effectiveness of the connected control paradigm are tested with simulation on a two-lane freeway stretch with intelligent vehicles randomly distributed among human-driven vehicles. Simulation shows that the connected VSL and vehicle control system improves traffic efficiency and sustainability; that is, total time spent in the network and average fuel consumption rate are reduced compared to (uncontrolled and controlled) scenarios with 100% human drivers and to uncontrolled scenarios with the same intelligent vehicle penetration rates.