智能型转辙机通用测试台的研制

针对检修所配置的转辙机测试台功能单一,无法满足对所有系列转辙机的测试,特别是对双机牵引类型转辙设备无测试手段的问题,阐述了智能型转辙机通用测试台的功能、关键技术和系统组成。     

SVPWM逆变器死区补偿的研究与实现

分析了空间电压矢量脉宽调制（SVPWM）逆变器死区效应产生的原因及影响,根据死区效应及SVPWM的特点提出了电压补偿法。该方法无需增加硬件,实用性较强。仿真和实验结果验证了该方法的有效性。     

一种实用新型底盘装配支撑结构的开发

底盘装配支撑应用于商用汽车底盘装配与工程机械车辆底盘装配,属于装配线附属工装设施。底盘装配支撑结构的适用性、可靠性、耐久性关系到底盘装配线的运行安全与运行效率。文章结合公司在建底盘装配线工艺验证问题整改,对底盘装配支撑结构进行优化,开发出一种适用于驱动桥桥包支撑的实用新型支撑结构。     

地铁车辆段检修库移动式架车机的工艺分析

地铁车辆段检修库中移动式架车机是车体与转向架分解组装以及车底电器、制动等模块拆装的必备设备,移动式架车机以其适用车型广、组合灵活、成本低的特点,得到广泛应用,而移动式架车机要想实现上述功能,需要分析研究与之配套设施的工艺特点。提出移动式架车机在检修库中采用有检查坑和无检查坑的布置方案,通过分析总结后,认为临修库中设置移动式架车机时,采用无检查沟的形式,在架修库设置移动式架车机时,采用有检查坑的形式。     

连续箱梁支架预压技术

文章以郑西客运专线渭河特大桥工程为例,介绍了大型箱梁支架预压的工艺流程、预压荷载、加载范围及加载操作过程,提出了在加载过程操作中应注意的问题,为连续箱梁支架预压施工提供参考。     

Separation of car-dependent commuters from normal-choice riders in mode-choice analysis

The ever-increasing use of cars is a big problem in metropolitan areas. To manage the traffic stream and alleviate air pollution, most metropolitan governments are attempting to discourage the use of cars. Nevertheless, the results have not been satisfactory. It is well known that normal-choice riders choose their travel mode based on utility, which is determined by mode-specific impedances and individual characteristics. On the other hand, this study focuses on identifying car-dependent commuters who tend to keep driving cars regardless of the circumstances they are confronted with. For this study, psychometric factors characterizing car-dependent commuters were investigated. However, the performance of the mode-choice model was not sufficiently enhanced despite incorporation of the psychometric factors. The performance improved considerably when the car-dependent commuters were excluded. Based on psychometric factors, the support vector machine successfully separated the car-dependent commuters from normal-choice riders.

基于支持向量机的动力电池故障诊断

电池故障诊断是电池管理系统中一项十分重要的技术。针对电池故障和电池输出状态量之间不确定的关系,采用模糊逻辑可以对模糊关系进行准确描述。选用合适的隶属度函数来表示输出的电压、电流信号,用模糊数学理论表示不确定的电池故障与电池输出状态量之间的关系,生成模糊数据库,用支持向量机对数据进行训练和测试,由结果可知该方法有较高的准确性。     

柔性自动化气密性检测系统实例

文章以OP70缸盖中间测漏机为实例,首先阐述了气密性检测技术以及自动化测试系统的特点,然后介绍了该设备的基本组成,并着重介绍了该设备的柔性化气密性测试结构。     

对大吨位压力试验机改造方案的分析

依据TB/T、2331--2004《铁路桥梁盆式橡胶支座》的要求，对机车车辆检验站10000kN试验机进行改造。主要是通过设计工装使大吨位的万能试验机满足桥梁支座的压转试验、摩擦系数试验的要求。重点介绍了零件的设计过程和对方案的分析。     

Autonomous vehicle self-localization based on abstract map and multi-channel LiDAR in urban area

Accurate vehicle self-localization is significant for autonomous driving. The localization techniques based on Global Navigation Satellite System (GNSS) cannot achieve the required accuracy in urban canyons. On the other hand, simultaneous localization and mapping (SLAM) methods suffer from the error accumulation problem. State-of-the-art localization approaches adopt 3D Light Detection and Ranging (Lidar) to observe the surrounding environment and match the observation with a priori known 3D point cloud map for estimating the position of the vehicle within the map. However, storing the massive point cloud needs immense storage on the vehicle, or it should be stored on servers, which makes the simultaneous downloading of the map by multiple vehicles another challenge. In this study, rather than employing the point cloud directly as the prior map, we focus on the abstract map of buildings, which is easy to extract, and at the same time apparently observable by Lidar. More especially, we proposed vehicle localization methods based on two different abstract map formats representing urban areas. The first format is the multilayer 2D vector map of building footprints, which represents the building boundaries using vectors (lines). The second format is the planar surface map of buildings and ground. These map formats share the same idea that the uncertainty (deviation) of each vector or planar surface is calculated and included in the map. Later in the localization phase, the observed data from Lidar is matched with the abstract map to obtain the precise location of the vehicle. Experiments conducted in a dense urban area of Tokyo show that even though we significantly shrank the map size, we could preserve the mean error of the localization.