A review of artificial intelligence applications in high-speed railway systems

In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions.

Dynamics and Fault Diagnosis of Railway Vehicle Gearboxes:A Review

The railway vehicle gearbox is an important part of the railway vehicle traction transmission system which ensures the smooth running of railway vehicles.However,as the running speed of railway vehicles continues to increase,the railway vehicle gearbox is exposed to a more demanding operating environment.Under both internal and external excitations,the gearbox is prone to faults such as fatigue cracks,and broken teeth.It is crucial to detect these faults before they result in severe failures and accidents.Therefore,understanding the dynamics and fault diagnosis of railway vehicle gearbox is needed.At present,there is a lack of systematic review of railway vehicle gearbox dynamics and fault diagnosis.So,this paper systematically summarizes the research progress on railway vehicle gearbox dynamics and fault diagnosis.To this end,this paper first summarizes the latest research progress on the dynamics of railway vehicle gearboxes.The dynamics and vibration characteristics of the gearbox are summarized under internal and external excitations,as well as faulty conditions.Then,the stateof-the-art signal processing and artificial intelligence methods for fault diagnosis of railway vehicle gearboxes are reviewed.In the end,future research prospects are given.

Key technologies and applications of intelligent dispatching command for high-speed railway in China

Purpose–The intelligent Central Traffic Control(CTC)system plays a vital role in establishing an intelligent high-speed railway(HSR)system.As the core of HSR transportation command,the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching.This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.Design/methodology/approach–This paper first briefly introduces the functions and configuration of the intelligent CTC system.Some new servers,terminals and interfaces are introduced,which are plan adjustment server/terminal,interface for automatic train operation(ATO),interface for Dynamic Monitoring System of Train Control Equipment(DMS),interface for Power Supervisory Control and Data Acquisition(PSCADA),interface for Disaster Monitoring,etc.Findings–The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans,safety control of train routes and commands,traffic information data platform,integrated simulation of traffic dispatching and ATO function.These technologies have been applied in the Beijing-Zhangjiakou HSR,which commenced operations at the end of 2019.Implementing these key intelligent functions has improved the train dispatching command capacity,ensured the safe operation of intelligent HSR,reduced the labor intensity of dispatching operators and enhanced the intelligence level of China’s dispatching system.Originality/value–This paper provides further challenges and research directions for the intelligent dispatching command of HSR.To achieve the objectives,new measures need to be conducted,including the development of advanced technologies for intelligent dispatching command,coping with new requirements with the development of China’s railway signaling system,the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

跨域杀伤网架构及其技术分析

在全域作战理论推动下,杀伤链正向更加复杂、更加多维的杀伤网发展。从作战概念入手,分析了杀伤网的运行特点,针对全域作战中跨域杀伤网构建问题,提出了体系能力服务平台+作战应用的系统架构,设计了相关智能体的职责分配和信息交互方法;从杀伤网构建和效能优化的角度,提出了基于作战资源可识别、可定义及可组合的能力生成机理,并对作战资源调用的合作博弈机制进行了探讨。最后,从技术实现角度,提出了智能体构建及智能体参数选择的方法,并分析了人工智能技术在跨域杀伤网构建过程中的赋能作用。

预警机装备形态演变的新特征

自1945年投入使用以来,预警机装备经过近80年的发展,其在作战体系和杀伤链构建中,经历了从低空补忙雷达向空中C2节点的转变。现今,一方面,有人预警机的核心节点作用愈发凸显,主要担负空战场管理任务;另一方面,无人化预警机形态正在加速出现,重点发挥预警探测而不是指挥控制作用,作为有人预警机的重要补充。在产品形态上,未来的预警机将具备敏捷性、协同性以及自主性等重要特征。

人工智能在信号控制系统的应用

随着现代社会科学技术水平不断提高,人工智能技术在许多领域都有了深入广泛的应用。大城市交通拥堵问题日益加剧,对信号控制智能化水平提出更高的要求。通过分析上海目前信号控制系统存在的问题,提出将人工智能技术应用到信号控制系统的设想,并对应用场景进行展望。智能信号控制系统是提高通行效率、缓解交通拥堵的重要抓手,是未来提升城市精细化交通管理水平的重要发展方向。

基于网络信息体系的全域联合指挥与控制技术及未来展望

面向现代战争需求,全域联合作战通过打破传统作战区域限制,能够实现不同军种和作战领域的信息共享、军事力量整合和协同作战,从而提升作战效率、增强指挥灵活性、优化资源配置。全域联合有诸多优势,使基于网络信息体系的全域联合指挥与控制技术成为研究重点。本文系统分析了全域联合指挥与控制的发展历程、技术应用、架构设计和关键技术,同时结合国外的研究现状探讨发展方向,旨在为全域联合指挥与控制技术的发展提供参考。

人工智能赋能军事技术举措和发展趋势分析

人工智能技术广泛运用于军事领域,显著提升了战斗效率,推动了军事技术的发展。文中对处于人工智能技术在军事领域研究和应用的领先地位的美国状况进行了详细讨论。具体针对人工智能技术在情报、监视和侦察、后勤支持、网络作战、指挥与控制、半自主和自主载具以及自主武器等领域的应用进行了深入分析,预测了未来人工智能技术在军事领域的发展趋势。最后指出对国内军事领域开展人工智能技术研究的指导和借鉴作用。

未来智能空战指挥控制关键技术发展思考

聚焦未来大国博弈环境下的空战对抗的新样式、新形态和新能力,分析了空战场指挥控制面临的挑战,思考了人工智能技术对于空战智能指挥控制变革的影响。首先,总结了以战斗机平台、机载电子设备和武器装备的能力演进为主的空战发展历程,给出了空战制胜机理的演变过程;然后,分析了新质作战概念和智能化技术对于未来智能空战的影响,阐述了未来智能空战的新形态;最后,总结了对手在智能空战项目布局和能力形成上的相关工作,提出了智能空战关键技术面临的问题及其发展思路。

地面无人分队智能化指挥控制系统设计

传统的指挥控制系统主要针对有人装备,正逐渐难以适应新形势下的陆战场有人/无人协同作战特点。针对未来高动态、强对抗和不确定任务的无人化陆战环境下的自主化、智能化指挥控制需求,亟需开展面向地面无人分队的智能化指挥控制系统研究。对有人/无人协同作战的人机协作式指挥流程进行分析,构建了无人化作战智能指挥控制系统体系结构,对人-机协作系统在整个作战任务剖面内的信息流与任务流,以及任务分工、协作方式、决策分配规则、权限及控制规则等进行了初步的探讨。并在此基础上构建了智能指挥控制系统仿真演示环境,为构建适应未来无人化陆战的有人/无人协同智能化指挥控制系统提供参考。

人工智能对指控领域的影响

人工智能技术的飞速发展,影响、制约、引导甚至主导现代作战方式。尤其在指控领域,人工智能技术通过指控系统与装备,深刻影响着指控活动各要素、各环节。然而,受限于人工智能技术新质性和军事系统特殊性,人工智能对指控的影响在非战争期间不易显性捕捉,难以显性度量。因此,从人工智能与指控的关系、人工智能对指控要素的影响方式、人工智能对指控的影响趋势、人工智能与指控协同进化面临的风险与挑战四个方面,系统挖掘人工智能对指控领域的作用机理。所得结论可以辅助军事人员更好地把控战场,把控战争,迎接智能化时代战争挑战。

路径规划及信号灯控制的智能优化

由于全智能化的交通控制系统尚未得到完全普及,道路交通资源占用时空二维不够均衡、城市交通规划策略与通行车辆规模不够匹配,导致城市交通拥塞、车辆准点率低等问题。针对上述问题,首先构建了基于服务员休假的多队列多服务员排队模型和级联队列的多跳排队模型,分析了在十字路口处及一般道路情况下车辆流量、信号灯时长与通勤时延的理论关系;然后提出了基于近端策略优化的路径规划及信号灯控制的智能优化方法,通过动态感知城市实时交通拥塞状态,联合规划车辆最优路径和控制信号灯最优时长,从而最大化车辆准点率。仿真结果表明,所提方法比于自适应高效联邦对比方法在时延性能方面提升了3倍以上,在车辆准点率方面提升了18%左右。

Energy-Efficiency Improvement in Mine-Railway Operation Using AI

The mining industry consumes an enormous amount of energy globally,the main part of which is conservable.Diesel is a key source of energy in mining operations,and mine locomotives have significant diesel consumption.Train speed has been recognized as the primary parameter affecting locomotive fuel consumption.In this study,an artificial intelligence(AI)look-forward control is developed as an online method for energy-efficiency improvement in mine-railway operation.An AI controller will modify the desired train-speed profile by accounting for the grade resistance and speed limits of the route ahead.Travel-time increment is applied as an improvement constraint.Recent models for mine-train-movement simulation have estimated locomotive fuel burn using an indirect index.An AI-developed algorithm for mine-train-movement simulation can correctly predict locomotive diesel consumption based on the considered values of the transfer parameters in this paper.This algorithm finds the mine-locomotive subsystems,and satisfies the practical diesel-consumption data specified in the locomotive’s manufacturer catalog.The model developed in this study has two main sections designed to estimate locomotive fuel consumption in different situations by using an artificial neural network(ANN),and an optimization section that applies a genetic algorithm(GA)to optimize train speed for the purpose of minimizing locomotive diesel consumption.The AI model proposed in this paper is learned and validated using real datasets collected from a mine-railway route in Western Australia.The simulation of a mine train with a commonly used locomotive in Australia GeneralMotors SD40-2(GM SD40-2)on a local railway track illustrates a significant reduction in diesel consumption along with a satisfactory travel-time increment.The simulation results also demonstrate that the AI look-forward controller has faster calculations than control systems based that use dynamic programming.

决策中心战的能力需求与技术支撑

为重建长期战略优势,美国率先提出的决策中心战作战新概念已经成为世界各军事强国的关注热点。分析了决策中心战的提出背景和原因,从深化认知决策优势和作战复杂性等方面剖析了其内涵机理,认识到强大的网络通信能力的支持是实现马赛克战或分布式控制的重要能力需求。在此基础上,重点分析了决策中心战在战役战术层6个方面的能力需求,并提出了未来支撑这些能力形成的先进技术,有助于全面把握以“决策中心战”为代表的新军事理论体系的构建与实践运行,为我军智能化建设提供借鉴。

运用改进磷虾群算法的自抗扰控制方法

为了提升自抗扰控制效果,提出了基于改进磷虾群算法的自抗扰控制方法.利用线性自抗扰控制技术,设计电力系统自抗扰控制器;利用扩张状态观测器估计系统总扰动,在系统控制量内加入前馈微分信号,通过该控制器的线性误差反馈律自抗扰控制电力系统,采用改进磷虾群算法优化该控制器的反馈比例增益与反馈微分增益,提升自抗扰控制效果.实验结果表明,在不同扰动时,应用本文方法自抗扰控制后,可有效降低电力系统稳态误差有效值与谐波畸变率.

人工智能技术在国外舰载武器系统中的应用浅析

近年来,人工智能技术广泛应用于国防等领域,并取得了相关突破。当前人工智能技术在舰载武器系统中的综合应用情况缺乏系统的总结与分析,在充分调研国外相关文献的基础上,总结阐述了人工智能技术在舰载武器系统中探测识别、指挥控制及火力打击等功能系统中的具体应用,并针对性地提出见解。最后,对人工智能技术在舰载武器系统中的应用进行总结,并提出了今后的发展趋势,以期为国内相关技术的应用和发展提供一定的参考。

人工智能在装甲火力与指挥控制领域的应用

人工智能在图像识别、语音识别、自然语言处理、机器翻译等民用领域已经取得重大进展,但在军事领域,尤其是装甲火力与指挥控制领域的落地应用较少。针对装甲装备分队作战的军事智能化需求,研究了人工智能在装甲火力与指挥控制领域的应用;探讨了智能的本质和人工智能的进化;分别研究了人工智能在装甲火力控制领域和装甲指挥控制领域的应用;讨论了军事人工智能应用所面临的一系列挑战,并给出下一步发展建议。

多架无人机协同作战智能指挥控制系统

给出一种基于Agent技术的多架无人作战飞机协同控制系统的设计方法,该系统由几类Agent构成:情报决策Agent、单机自主决策Agent、协同决策Agent等。由于利用了Agent的两大优良特性——自主性和协同性,系统能够控制多架无人作战飞机,各无人机对不断变化的战场环境也具有很高的适应性。

无传感器永磁同步电机矢量控制系统概述

永磁同步电机因其自身的一些优点 ,在国防、工农业生产和日常生活等方面获得越来越广泛的应用。同时无传感器永磁同步电机的矢量控制方法 ,也成为研究中的一个热点。文章首先简单介绍了永磁同步电机数学模型和矢量控制的基本原理 ,在此基础上又集中介绍了近十几年来提出的多种估算永磁同步电机转子位置和转速的方法 ,如利用反电动势的估算方法 ,观测器方法 ,模型参考自适应方法 ,高频注入方法等等。对其中较重要的方法进行了详细的分析 ,比较了各种方法的优缺点 。

故障诊断技术及其发展趋势

故障诊断就是通过对设备运行信息的检测、分析和处理,判别设备的工作状况,分析故障成因,预测劣化趋势,以达到提高设备效率和运行可靠性,防患于未然的目的。为此,比较系统地阐述了故障诊断的过程及其相关应用技术;论述了故障信号采集与处理等环节的主要技术和方法;介绍了故障诊断技术的发展概况;对故障诊断技术的发展趋势进行了探讨。