动态系统故障诊断的未知输入观测器组方法

介绍了动态系统故障诊断的未知输入观测器组方法的原理和设计步骤,对于线性离散定常系统,详细推导了基于矩阵束的克罗内克尔标准形变换的观测器设计算法,所得观测器对于指定故障敏感,对其他未知输入解耦,重复该设计过程,可得到观测器组,实现鲁棒的动态系统故障检测和分离,最后讨论了设计方法的有关问题。     

中压共轨系统油压控制中PID参数的整定方法

简要介绍了一种柴油机液力中压共轨系统的构成。在系统共轨管油压控制中引入遇限制削弱积分法,采样周期是从试验测出的阶跃响应曲线获取的,并考虑诸多的影响因素。采用正交试验方法安排试验来整定共轨油压PID参数,并用极差方法分析试验结果,从而获取PID参数的影响主次、影响规律及相互间的关系,最终获得某一工况下的PID最优参数。     

AN FFT-BASED SELF-SIMILAR TRAFFIC GENERATOR

IntroductionWhen modeling network traffic,packet ar-rivals are often assumed to be Poisson processes,because such processes have attractive theoreticalproperties. Recenet work,however,argues con-vincingly that local- area network traffic is muchbetter modeled using statistically self- similar pro-cesses[1] ,which have more different theoreticalproperties than Poisson processes. A subsequentinvestigation suggests that the same holds forwide- area network traffic[2 ,3 ] .The theory of self- sim…     

高速列车运行工况可视化系统的研究

介绍-种表现高速铁路运行状况的动画设计和制作方法.综合有关铁路线路各个分立数据库的内容,如:线路坡道、桥梁、隧道、车站、挖填方等,运用动画仿真技术,从纵断面的视角将各个数据库存储的线路属性参数在同一个画面上统一、关联地表现出来,达到直观便捷的表现效果.     

溶岩地区桩基础施工技术问题的探讨

石灰岩地区地质情况较复杂,对桥梁的基础施工带来困难和不利影响。介绍花清高速公路高架桥在石灰岩溶岩地区的桩基础施工技术。     

“博远一号”运输船改装设计

军用登陆艇改装为民用运输船,其设计总体改装方案、改装工艺是成功的,值得总结介绍。     

降雨入渗下裂土边坡水分运移时空特征与失稳机理

为探究降雨入渗下裂土边坡水分运移时空特征与失稳机理, 自主研制了足尺模型试验系统和光纤布拉格光栅(FBG)深部柔性位移系统, 对边坡渐进破坏进行了全过程、多物理量联合监测, 揭示了降雨入渗作用下裂土边坡的渐进变形和破坏演化模式; 基于裂土边坡的渐进破坏模式, 提出了土体饱和比概念, 将裂隙深度范围滑体分为饱和层和非饱和层; 以土体饱和度变化描述了含随机分布裂隙的边坡水分运移规律, 并结合刚体极限平衡法探讨了由裂隙控制的边坡失稳机制。研究结果表明: 对于未形成裂隙的边坡, 连续降小雨时浅层变形受表层基质吸力控制; 裂隙形成后, 雨水沿裂隙快速入渗形成暂态饱和区, 导致基质吸力降幅达82.50%~87.14%, 而由其贡献的抗剪强度迅速损失, 从而形成初期溜滑、片蚀等浅层变形, 降雨停止后坡体仍处于蠕变过程, 坡脚与坡顶位移增幅分别为23.40%和19.39%;蒸发后裂隙规模发展增大了雨水对渗流场的影响范围和边坡破坏规模; 土体经历胀缩、蠕变而变得松散, 裂缝区深部土体体积含水率较初始状态的增幅为205.7%;同一降雨条件下, 初始裂隙深度愈深, 稳定系数愈低, 破坏愈快; 对具有同一裂隙深度的边坡, 其稳定系数随土体饱和比的增加逐渐降低, 土体饱和比增长愈快, 表征边坡内部出现大面积连通型饱和区, 这是裂土边坡出现整体失稳的主要原因。      

大连新建地铁对公交出行选择的影响

为了分析城市新建地铁项目对居民公共交通出行的影响,改善公交服务水平,提高公共交 通的分担率,针对大连市新建地铁线路展开研究。以大连市地铁1 号线沿线站点作为研究区域, 采用SP （Stated Preference） 调查方法,收集了300 名地铁沿线居民对常规公交以及新建地铁两种 出行方式的选择数据。通过建立二项Logit 模型,分析出行成本、换乘时间等选择方案特性变 量,出行特性变量以及出行者特性变量对于居民出行方式选择行为的影响,并计算弹性值及模型 精度。结果表明,通过调整出行成本及换乘时间可有效提高地铁分担率。由此提出相关政策建 议：对于出行成本,可从出行者年龄及出行次数两方面制定不同的优惠政策;对于换乘时间,可 从提高可达性、完善购票系统以及调整发班频率三方面进行改善。     

Geometric calibration algorithm of polarization camera using planar patterns

Polarization pattern provides additional information besides spectral signatures. It can be used in many applications, such as navigation, defect detection and object identification. A novel polarization camera composed of four synchronized cameras is proposed, and it can realize real-time polarization measurement. This study particularly concentrates on the geometric calibration of the system. The projection model is analyzed and the multi-camera calibration algorithm is proposed. Firstly, each camera is calibrated separately using planar patterns, and then the geometric calibration algorithms are performed. Due to the geometrical constraint, a global optimization method results in smaller estimation uncertainties. A mean rotation error of 0.025° and a mean translation error of 0.26mm are achieved after geometric calibration. The images are rectified to establish a correspondence among cameras and are combined to acquire the polarization measurement. The polarization pattern of the skylight is measured by the system and the results are consistent with the previous studies.     

Fault diagnosis for wind turbine based on improved extreme learning machine

A fault diagnosis method based on improved extreme learning machine (IELM) is proposed to solve the weakness (weak generalization ability, low diagnostic rate) of traditional fault diagnosis with feedforward neural network algorithm. This method fuses signal feature vectors, extracts six parameters as the principal component analysis (PCA) variables, and calculates correlation coefficient matrix among the variables. The weight values of control parameters in the extreme learning model are dynamically adjusted according to the test samples’ constantly changing. Consequently, the weight fixed drawback in the original model can be remedied. A fault simulation experiment platform for wind turbine drive system is built, eight kinds of fault modes are diagnosed by the improved extreme learning model, and the result is compared with that of other machine learning methods. The experiment indicates that the method can enhance the accuracy and generalization ability of diagnosis, and increase the computing speed. It is convenient for engineering application.