面向智能船舶的容错卡尔曼融合估计方法

针对智能船舶多传感器系统因未知海洋环境干扰和设备间干扰等因素导致的一个或数个传感器产生随机间歇性故障从而导致融合估计结果出现偏差甚至失真的问题,设计1种基于四分位滤波的容错方法,并针对该方法导致的观测时滞问题设计1种预报方法,提前预报观测值,进而抵消容错方法导致的时滞问题。此外,针对多传感器之间的互协方差难以准确估计的问题,采用CI融合估计方法进行融合估计。为验证算法的有效性和融合估计的精度,对带有间歇性故障的两传感器系统进行仿真试验,并与按矩阵、按对角阵和按标量3种分布式融合估计方法得到的结果进行对比。4种方法的均方误差系数大小对比结果显示,对于带间歇性故障的多传感器系统,设计的融合滤波不仅具有鲁棒性,而且具有较高的融合精度。     

一种基于数据挖掘的GIS及在航海中的应用

根据聚类分析方法中密度凝聚的思想，提出一种新的复合聚类分析算法，进一步将这种算法用于地理信息系统的数据挖掘，并应用于船舶航线的自动设计。     

Data Fusion-Based Traffic Density Estimation and Prediction

Traffic congestion has become a major challenge in recent years in many countries of the world. One way to alleviate congestion is to manage the traffic efficiently by applying intelligent transportation systems (ITS). One set of ITS technologies helps in diverting vehicles from congested parts of the network to alternate routes having less congestion. Congestion is often measured by traffic density, which is the number of vehicles per unit stretch of the roadway. Density, being a spatial characteristic, is difficult to measure in the field. Also, the general approach of estimating density from location-based measures may not capture the spatial variation in density. To capture the spatial variation better, density can be estimated using both location-based and spatial data sources using a data fusion approach. The present study uses a Kalman filter to fuse spatial and location-based data for the estimation of traffic density. Subsequently, the estimated data are utilized for predicting density to future time intervals using a time-series regression model. The models were estimated and validated using both field and simulated data. Both estimation and prediction models performed well, despite the challenges arising from heterogeneous traffic flow conditions prevalent in India.     

北京市交通信号管理与控制平台设计及应用

在分析现有交通信号系统的特性以及存在问题的基础上,以对现有信号系统进行有效整合、综合利用交通流数据、提高交通信号控制的管理水平为目标,设计了1种集成的交通信号控制平台,并给出了平台在北京市交通信号管理与控制系统中的应用。     

动车基地调度集中系统

在对动车基地调度业务特点进行分析的基础上,介绍了动车基地调度集中系统的总体架构、应用功能以及对外接口。本系统的实现为同类铁路调度指挥系统的设计与开发提供了重要的参考,具有十分广阔的运用前景。     

聚合物基体复合材料与金属的连接工艺综述

复合材料等轻量化材料在汽车制造领域的大量应用,为异种材料连接技术带来了新的机遇与挑战。在国内外学者的不懈努力下,越来越多的连接技术涌现出来。根据连接过程中不同的热量产生机制,可将复合材料与金属之间的连接方法分为机械连接、胶接及熔焊连接3个类别。然而,由于异种材料在理化特性方面存在着巨大的差异,其连接技术中存在的问题制约了复合材料与传统金属材料的混合使用。对3种连接工艺进行了综述,并比较其应用现状与优缺点,为选择恰当的连接工艺提供参考。     

Q235钢焊接熔合区在混合菌共同作用下的腐蚀行为

通过观察腐蚀形貌,测量极化曲线和阻抗谱,研究了Q235钢熔合区在SRB和V.natriegens共同作用下的腐蚀行为。研究表明,熔合区的腐蚀程度,单一菌溶液中,SRB大于V.natriegens,混合菌溶液大于单一菌;混合菌溶液中SRB和V.natriegens表现出协同作用,加速试样的腐蚀;试样的耐腐蚀性能,熔合区小于焊缝区小于母材区。     

Data fusion algorithm for macroscopic fundamental diagram estimation

A promising framework that describes traffic conditions in urban networks is the macroscopic fundamental diagram (MFD), relating average flow and average density in a relatively homogeneous urban network. It has been shown that the MFD can be used, for example, for traffic access control. However, an implementation requires an accurate estimation of the MFD with the available data sources.Most scientific literature has considered the estimation of MFDs based on either loop detector data (LDD) or floating car data (FCD). In this paper, however, we propose a methodology for estimating the MFD based on both data sources simultaneously. To that end, we have defined a fusion algorithm that separates the urban network into two sub-networks, one with loop detectors and one without. The LDD and the FCD are then fused taking into account the accuracy and network coverage of each data type. Simulations of an abstract grid network and the network of the city of Zurich show that the fusion algorithm always reduces the estimation error significantly with respect to an estimation where only one data source is used. This holds true, even when we account for the fact that the probe penetration rate of FCD needs to be estimated with loop detectors, hence it might also include some errors depending on the number of loop detectors, especially when probe vehicles are not homogeneously distributed within the network.     

基于中心差分卡尔曼滤波的车速估计研究

针对车辆行驶过程中车速估计问题,论文基于中心差分卡尔曼滤波理论设计了车速的估计算法。建立了非线性三自由度车辆估算模型,根据纵向加速度、侧向加速度和方向盘转角低成本传感器信号的信息融合,实现对车速的准确估计,应用CarSim与Matl ab/Simulink联合仿真实验对算法进行验证。结果表明:估计算法能够准确估计车辆行驶过程中的纵向车速、侧向车速和质心侧偏角。     

基于多传感器信息融合技术的轨道交通车站设备故障诊断

本文在分析了轨道交通车站设备故障诊断的特点和多传感器信息融合技术的基础上,总结了适合于故障诊断的信息融合典型结构以及基于信息融合的故障诊断系统结构。该结构在轨道交通车站设备故障诊断系统中具有普遍意义,实用性强。