下一代高速铁路异构网络切换安全认证

近年来,随着高速铁路无线通信技术的快速发展, GSM-R无线通信系统将逐步向LTE-R系统演进。在此演进过程中存在GSM-R和LTE-R长期共存的局面,如何实现高速铁路无线通信异构网络之间的快速切换和安全认证成为铁路无线通信研究的热点问题。针对高速铁路无线通信异构网络切换认证过程中,存在安全性低和认证开销高等问题,提出了一种适用于下一代高速铁路异构网络的轻量级切换安全认证方案。首先,采用哈希函数等操作生成切换请求Token和异构网络切换认证码PASS,实现了用户身份匿名性和可追溯性等安全要求,并且高速列车无需多次注册就可实现异构网络间的无缝切换。其次,设计了基于椭圆曲线密钥交换的轻量级切换算法,完成了高速列车与目标基站的相互认证和密钥协商,降低了计算开销和通信开销,实现了会话协商密钥的前后向安全性。最后,采用形式化方式BAN逻辑进行了安全性验证,并使用朔黄铁路LTE-R线路实测数据进一步对本文所提方案的有效性进行了验证,分析得出所提方案能够满足可追溯性、匿名性、抗伪装用户攻击、抗中间人攻击和抗重放攻击等安全特性。性能分析表明,本文方案在通信开销和计算开销方面较比较方法性能更优,能够满足...     

移动闭塞条件下基于双曲列控策略的发车间隔时间计算

列车间隔时间关乎铁路行车安全和效率。对未来铁路移动闭塞系统发车间隔时间的科学计算进行探讨,引入了能够反映经验丰富司机驾车列车优化行为的基于双曲函数的列车行为控制模型;然后,讨论了列车分段运动方程和车站发车作业、进路解锁等环节,以及各种误差因素,并将它们与基于双曲函数的列车行为控制模型有机结合起来,建立了计算移动闭塞条件下车站发车间隔时间的数学模型,给出了两种不同情形的车站发车间隔时间计算方法,数值仿真试验验证了算法的有效性和可行性。对移动闭塞条件下车站发车环节的列车行为控制和行车组织有较大参考价值。     

基于Zigbee技术的应答式铁路安全施工预警系统

铁路施工的人身安全是铁路维护的一个重要环节,人们曾为此做过不懈的努力,提供了多种解决方案,在保证铁路安全运行方面效果显著,但随着列车提速,对列车安全运行提出了新的要求。本系统基于Zigbee技术,构建了一套应答式列车接近预警系统,为路轨维护人员的人身安全及列车的安全运行提供了一种较好的解决方法。     

面向货运列车的物联网实时在线监控系统设计

针对铁路货车行车安全状态监测系统的应用需求,设计一种基于物联网技术的货运列车监控系统.系统采用ZigBee短距离无线通信技术搭建无线传感网络,通过各节车辆的传感器节点采集数据发送到机车监控平台,然后通过GPRS网络与地面监控中心进行通信,实现车地数据的实时传输.经测试,系统达到了良好的实时在线监测效果,在铁路货车行车安全监测领域具有广泛的应用前景.     

基于STM32的轨道方向不平顺检测系统设计

轨道不平顺是影响列车乘坐舒适性和平稳性的主要激励源,对轨道不平顺信号进行准确检测和有效的分析处理,以尽可能提高铁路维修效率,保障高速列车行车安全。为了准确检测轨道方向不平顺信号,基于惯性基准法原理,研制了以STM32F103 Cortex-M3 ARM处理器为控制核心的自动化检测系统。系统调理采集包括伺服加速度计、陀螺仪、倾角仪等多路传感器转换而来的模拟信号,然后传输到车载服务器中分析处理。检测结果以实时波形图的形式显示,能够准确有效地判断不平顺状态。     

New bounds and algorithms for the transshipment yard scheduling problem

In a modern rail?Crail transshipment yard huge gantry cranes transship containers between different freight trains, so that hub-and-spoke railway systems are enabled. In this context, we consider the transshipment yard scheduling problem (TYSP) where trains have to be assigned to bundles, which jointly enter and leave the yard. The objective is to minimize split moves and revisits. Split moves appear whenever containers have to be exchanged between trains of different bundles, whereas revisits occur if a train has to enter the yard twice, because some container dedicated to this train was not available during its first visit. We extend the basic TYSP, so that additional real-world requirements of modern rail?Crail yards, e.g., the one currently constructed in Hannover-Lehrte, are considered. We provide complexity proofs for different problem settings and present several heuristic procedures as well as one exact algorithm. The paper concludes with computational results showing the efficiency of the proposed algorithms.     

列车运行网络抗毁性能的量化研究*

为尽可能减少由于自然灾害导致铁路运输受阻甚至中断情况下受影响的列车数,提出了对现有列车运行方案以抗毁性优化为目标的量化分析方法.首先基于当前列车运行方案建立列车运行网络模型,该模型以实际铁路站点为节点,以实际铁路线为边,以每条边开行的列车数量为边权重;随后提出了一个称之为度权效应的抗毁性评价指标,并以该评价指标为目标函数,使用改进粒子群算法对网络权重进行优化.仿真结果得出了优化前后列车运行网络的抗毁性评价值分别为0.8881和0.9063,表明可通过量化分析方法来刻画列车运行网络的抗毁性能.     

Security requirement derivation by noun–verb analysis of use–misuse case relationships: a case study using positive train control

Use cases and misuse cases, respectively, state the interactions that an actor can have and a mal-actor be prevented from having with a system. The cases do not specify either the security requirements or the associated attributes that a system must possess to operate in a secure manner. We present an algorithmic, domain-independent approach rooted in verb–noun analysis of use cases and misuse cases to generate system requirements and the associated security attributes. We illustrate the utility of this general five-step method using Positive train control (PTC) (a command and control system used to navigate trains in a railway grid) as a case study. This approach allows the designer to protect against the effect of wireless vulnerabilities on the safety of PTC systems.     

铁路道口列车运行安全监测系统的研究与应用

为保障铁路道口行车安全,利用移动数字通信公网的互联网接入平台通用分组无线业务(general packet radio service,简称GPRS)作为通讯手段,成功研发出一套全新的铁路道口行车安全监测系统;该系统不仅能够实时显示铁路道口部位列车运行情况,还可以结合列车行进位置,将监测数据进行信息化处理,并利用数据分析功能,对可能出现的安全问题发出警告;将这项技术用于列车与铁路道口进行试验,结果证明：当系统监测到电气特性指标超出安全范围或者是道口信号设备出现问题时,能够及时向工作人员发出警报,根据列车进出道口状态及运行状态迅速做出相应的处理。     

A fuzzy Petri net model to estimate train delays

Even with the most accurate timetable, trains often operate with delays. The running and waiting times for trains can increase unexpectedly, creating primary delays that cause knock-on delays and delays for other trains. The accurate estimation of train delays is important for creating timetables, dispatching trains, and planning infrastructures. In this work, we proposed a fuzzy Petri net (FPN) model for estimating train delays. The FPN model with characteristics of hierarchy, colour, time, and fuzzy reasoning was used to simulate traffic processes and train movements in a railway system. The trains were coloured tokens, the track sections were termed places, and discrete events of train movement were termed transitions. The train primary delays were simulated by a fuzzy Petri net module in the model. The fuzzy logic system was incorporated in the FPN module in two ways. First, when there were no historical data on train delays, expert knowledge was used to define fuzzy sets and rules, transforming the expertise into a model to calculate train delays. Second, a model based on the Adaptive Network Fuzzy Inference System (ANFIS) was used for systems where the historical data on train delays were available (from detection systems or from the train dispatcher’s logs). The delay data were used to train the neuro-fuzzy ANFIS model. After the results of the fuzzy logic system were verified, the ANFIS model was replicated by a fuzzy Petri net. The simulation was validated by animating the train movement and plotting the time-distance graph of the trains. Results of the simulation were exported to a database for additional data mining and comparative analysis. The FPN model was tested on a part of the Belgrade railway node.     

Cloud-based approach for automatic CNC workpiece origin localization based on image analysis

Computer vision applications in the industry have been a constant field of research in academia. Industrial daily challenges such as quality inspection, object detection, and measurement are examples of situations where some automation could be done by using computer vision techniques. In this paper, a cloud-based approach of an automatic system based on stereo vision and image analysis has been developed to automate a daily routine present in machining companies: workpiece referencing. The proposed architecture uses two cameras mounted in the spindle of a machining center. All images are processed in custom software, running on the cloud, to return the position of the Workpiece Coordinate System (WCS) directly to the Computer Numerical Control (CNC) machine controller. Experimental results validate the application of the proposed architecture in a real machining process machine.     

高速列车牵引系统故障诊断与预测技术综述

高速列车因其舒适、便捷、安全和准时, 已成为我国主流的城际间交通工具.CRH(China railway high- speed)动车组高速列车是一个大型复杂的机电耦合系统,作为其重要组成部分,牵引控制系统的可靠性对于高速列车的安全运行至关重要.随着在轨运行时间的增长,牵引控制系统中的很多部件都会发生不同程度的性能衰退,并引发各种故障,给高速列车的安全运行带来潜在的危险.鉴于此,针对牵引变压器、牵引变流器(整流器、逆变器)、牵引电机、转向架系统、牵引/制动控制单元等与高速列车牵引系统相关的重要部件和单元的故障诊断、容错控制与预测方法进行现状调研和分析,并对每种方法的基本思路、现阶段进展以及适用条件等进行了介绍,最后陈述了高速列车牵引控制系统故障诊断与预测领域尚待解决的问题.     

海铁联运港口混合作业模式下轨道吊与集卡协同调度

在集装箱海铁联运港口中,铁路作业区作为连接铁路运输和水路运输的重要节点,其装卸效率将影响集装箱海铁联运的整体效率.首先,对比分析了"船舶-列车"作业模式和"船舶-堆场-列车"作业模式的特点,并结合海铁联运港口实际作业情况提出了混合作业模式.然后,以轨道吊完工时间最短为目标构建混合整数规划模型,既考虑了班列和船舶的作业时...     

Vision-guided tripod material transport system for the packaging industry

A new lightweight parallel kinematic serves as the basis for a material transport system designated for the automated supply of packaging machines with the necessary paper and foil material. The manipulator, a modified Stewart platform, resembles an overhead tripod and is equipped with an air compressor and a PC-based control with a multitasking real-time operating system. It travels on a gantry railway, using on-board visual sensors for the location of the bobbins with packaging material that are to be transported. The intelligent sensors enable the manipulator to locate the proper bobbin in the quasi-disordered arrangement, depalletize it and transfer it to the requesting machine.     

A distributed constraint-based scheduler

This paper presents the design and implementation of a distributed advisory system which helps different human experts in the management and control of traffic within railway stations and along railway branches. Our approach allows the management of a whole railway line in a modular, expandable and scalable way. The scheduling of trains along a railway line is performed by several modules each one controlling a certain number of resources. These modules solve the scheduling of trains by interacting and communicating with each other. Each module has to deal with temporal constraints, priority between trains and constraints due to the structure of the station and railway branches. Our approach is based on the constraint logic programming (CLP) paradigm for solving the constraints involved in the problem. Therefore, this paper shows the versatility and adequacy of the CLP approach for the problems of this type.     

具有极大时间约束的轨道交通系统的周期分析

运用极大–加代数方法研究具有极大时间约束的轨道交通系统的周期运行规律.分别建立具有两个车站的双回路城际轨道交通系统和具有n个车站的单回路城市轨道交通系统的极大–加线性模型.对于前者,运用系统状态矩阵的周期性,证明各个车站第k次与第(k+2)次的发车时间间隔相同;对于后者,运用状态变量的线性替换,证明在任何初始状态下,系统经过一次循环便可进入周期稳态运行,即列车连续两次到达同一车站的时间间隔相同.周期时间分析有利于轨道交通系统列车时刻表的编排和周期运行方案的设计.为验证本文结果的实用性和有效性,给出周期时间分析在列车调度和线路规划中的应用例子.     

列车安全距离控制形式化建模与验证

随着我国铁路的迅速发展,对列车运行安全性的要求越来越高。采用Event-B形式化建模方法研究了高速列车安全距离控制形式化验证问题,以Event-B形式化仿真工具Rodin为基础,通过结合多智能体理论,引入感知决策法则,实现了无线闭塞中心(RBC)与列车的车地通信,建立了多列车运行的安全距离控制模型。仿真研究了高速列车最小间隔追踪控制运行,对列车安全距离控车行为进行了形式化建模并进行了POs证明义务验证。仿真结果表明,对于CTCS列车控制系统的复杂逻辑关联行为,采用提出的Event-B和多智能体系统(MAS)结合的形式化验证方法,可进行系统规范的模型验证,对于复杂系统的逻辑验证有较强的实际意义。     

基于数据驱动的CRH高速列车悬挂系统早期故障检测

作为CRH(China railway high-speed)高速列车的重要组成部分,悬挂系统的可靠性对列车的安全运行和乘坐舒适性具有重要意义,为此,利用悬挂系统传感器数据,提出一种基于数据驱动的早期故障检测方法.首先,根据系统动态搭建列车悬挂系统Simpack模型,其中作动器的主动控制力作为系统输入,轨道不平顺由不平...     

Feature fusion for basic behavior unit segmentation from video sequences

It has become increasingly popular to study animal behaviors with the assistance of video recordings. An automated video processing and behavior analysis system is desired to replace the traditional manual annotation. We propose a framework for automatic video based behavior analysis systems, which consists of four major modules: behavior modeling, feature extraction from video sequences, basic behavior unit (BBU) discovery and complex behavior recognition. BBU discovery is performed based on features extracted from video sequences, hence the fusion of multiple dimensional features is very important. In this paper, we explore the application of feature fusion techniques to BBU discovery with one and multiple cameras. We applied the vector fusion (SBP) method, a multi-variate vector visualization technique, in fusing the features obtained from a single camera. This technique reduces the multiple dimensional data into two dimensional (SBP) space, and the spatial and temporal analysis in SBP space can help discover the underlying data groups. Then we present a simple feature fusion technique for BBU discovery from multiple cameras with the affinity graph method. Finally, we present encouraging results on a physical system and a synthetic mouse-in-a-cage scenario from one, two, and three cameras. The feature fusion methods in this paper are simple yet effective.