青藏铁路大风监测预警与行车指挥系统研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
恶劣风环境对铁路运输危害巨大,不仅损坏铁路设备、导致铁路网瘫痪,甚至造成人员伤亡。青藏铁路的格尔木至拉萨段正位于青藏高原腹地,气候复杂,极端天气事件频繁发生,给铁路安全运营带来严重威胁。研究解决包括新疆、青藏高原及东部沿海受台风影响地区等国内所有风区铁路的问题,确保恶劣风环境下的铁路运输安全,并尽可能实现铁路畅通,是铁路行业当前的一项重要任务。本文是在国家“十一五”支撑计划和铁道部下达的青藏铁路大风环境行车安全问题多个重点课题研究的基础上,针对青藏高原铁路风环境的特点,研究建立一套能适应青藏铁路特殊要求,从实时大风监测预警到形成列车运行速度限制指令、并能实现及时与通过风区的列车进行信息交换的大风监测预警系统,为列车安全通过风区以及大风环境下行车指挥调度提供有效决策依据和手段。
     针对青藏铁路沿线特殊风环境,确定青藏铁路大风监测预警与行车指挥系统总体设计思路,对格—拉段沿线风区子域划分及长距离实时风速采集、传输、存储技术,列车—大风—路况等多源信息融合与集成处理技术,风区列车运行实时预警与指挥决策技术,大风监测预警与行车指挥系统诊断维护与可靠性技术等进行了深入研究,提出了大风监测预警与行车指挥系统总体技术方案,构建了系统的主要功能模块。
     利用网络通讯与控制相关先进技术,在世界上首次建成辖域达1120km的高原铁路长大风区大风连续监测网络体系,集成了沿线大风连续监测系统网络、铁道部TMIS和TDCS系统网络、格拉段列车行调指挥系统网络,实现了整个网络体系所属系统间的数据高速、实时通讯功能。构建的西宁海量数据处理系统,实现了网络体系结构中所有系统的来源数据信息的实时储存与分析处理。
     对青藏铁路沿线各测风站位置及其辖域风区的风速、路况、列车等相关信息需要融合进行综合分析,建立了青藏铁路列车—大风—路况等多源信息融合处理方法,包括测风站位置—大风变化规律—路况信息融合,瞬时风—平均风—极大风—路况信息融合,铁路TMIS与TDCS系统信息融合,大风—列车气动性能—列车动力性能信息融合。
     通过上述各种信息融合处理,得到青藏铁路特殊风环境下的列车安全运行临界速度,进一步研究定出风速—路况—车外型与质量不同组合状态的列车安全运行速度限值。据此建立以车辆倾覆系数为主要运行安全评判准则的“决策模型”,即青藏铁路各测风站辖域内结合路况的各种风速—车型—车辆质量耦合、共计74880种工况的“工程化”限速算法。该算法实时计算出当前位于相关测风站辖域适合列车运行的“工程化”速度,成为实时预警与指挥青藏铁路恶劣风环境下安全行车决策的依据,发出限速指令,该指令通过列车行调指挥系统网络实时指挥当前列车以允许的速度安全通过其所在风区或至指定地点待避。
     研发了具有自主知识产权的高原铁路大风监测预警与行车指挥系统应用软件。包括高原铁路大风行车指挥软件、高原铁路大风实时监测软件、高原铁路大风列车实时限速计算软件、强侧风下列车倾覆稳定性计算软件、高原铁路动态编组监视软件、高原铁路大风无线传输控制软件、高原铁路大风数据处理分析软件、高原铁路大风实时预测分析软件。
     针对高原铁路恶劣气候下系统运行的高可靠性要求,实现了系统运行状态远程自动监测、控制以及故障状态信息自动储存等功能,构建了高原铁路大风监测预警与行车指挥系统可靠性运行保障体系,确保了高原铁路大风监测预警与行车指挥系统全天候高可靠性运行。
     高原铁路大风监测预警与行车指挥系统,自2006年7月通车不间断运营至今,经过两年应用考验,系统稳定可靠,已多次指挥列车停轮和限速,有效地保障了青藏铁路列车运行安全和运输效率,为预防青藏铁路大风危及行车安全提供了保障。建成的系统对风向多变,难以在线路两侧修建挡风墙的风区铁路,提供了一种保障大风环境下行车安全的有效手段,为解决我国所有风区铁路的行车安全问题奠定了重要基础。
Bad wind environment endangers railway transportation enormously. It not only damages railway equipment, causing paralysis of the railway network, but also causes casualties. Qinghai-Tibet Railway from geermu to Lasa with complex climate locates in the hinterland of Qinghai-Tibet Plateau and extreme weather events occurr frequently there, bringing a serious threat to the safe railway operation. The study solves Xinjiang, Qinghai-Tibet Plateau, the eastern coastal areas which affected by typhoons and all domestic rails in other wind zones. It is the present important task of railway industry to ensures the railway transport safety under bad wind conditions and try to make the railway unblocked. Based on the national "Eleventh Five-Year" support plan and some key research projects under the strong windy environment of Qinghai-Tibet railway traffic safety which was issued by the Ministry of Railways, this article establishes a series of winds monitoring and warning system for the characteristics of Qinghai-Tibet Railway's windy environment. The system adapts to Qinghai-Tibet Railway special request, from the real-time monitoring and warning to the formation of speed limit commands for trains to run, and can achieve a timely information exchange of the train through the wind zone, in order to safe passage of trains through the wind zone and to provide an effective basis for decision-making and means for running trains command under windy conditions.
     The overall design idea is determined that wind monitoring and warning and running trains command system of the Qinghai-Tibet railway driving for the special wind environment along the Qinghai-Tibet railway. The thorough researches are made that include the sub-domain division in the ge-la section along the wind zone, long-distance and real-time wind speed collection, transmission, storage technology, train-wind-road and multi-source information fusion and integration processing technology, train running in the wind zone real-time warning and command decision techniques, wind monitoring and warning and driving command system's diagnosis and maintenance and reliability technology and so on. The overall technical plan of wind monitoring and warning and traffic control system is put forward. The main modules of the system are built.
     The plateau railway continuous monitoring network system in long strong wind areas, whose scope reaches 1120km is firstly built up using the network communication and control related to advanced technology. The system integrates continuous monitoring of the wind along the system network, the Ministry of Railways TMIS and TDCS Network and Ge-La section Train line adjustment command system network. The whole network system of data between systems owned high-speed, real-time communication functions are realized. Construction of Xining Hai amount of data processing systems achieve a network architecture in the source of all systems of real-time data storage and analysis and processing.
     All measuring wind-speed stations'location along the Qinghai-Tibet railway and the imformation fusion of the wind speed, road, train and other related information in scope fetch are analyzed comprehensively. The Qinghai-Tibet Railway trains-high winds-roads and other multi-source information fusion methods are established, including the fusion of measuring the wind station location-the variation of wind-traffic information, the fusion of instantaneous wind-average wind-maximum wind-traffic information, the information amalgamation of railway TMIS and TDCS system, and the information fusion of the high wind-the aerodynamic performance of the train-the power performance of the train.
     By processing various information above, it gets the critical velocity of train operation safety on Qinghai-Tibet railway under special wind conditions. Further more we study and set limit speed of train operation safety under different combination formats of wind speed, railway condition, appearance of trains and quality. According to all above, "decision-making model" with vehicle overturning factor as its main judging criteria is established, which has 74880 kinds of working conditions totally. The algorithm calculates the current real-time engineering for the train running speed in the relevant wind measurement stations which becomes basis for a real-time warning and command of the Qinghai-Tibet railway under the harsh wind environment in decision-making based on operation safety. It sends out a speed limit instruction which conducts current trains to pass the wind area at an allowable speed safely or arrives at an assigned point to avoid the wind by the command system network of operation of trains.
     The paper developes strong wind monitoring and train traffic control system application software for the plateau railway which has independent intellectual property rights. It includes plateau railway strong wind train traffic control system, monitoring and warning system, real-time limit train speed calculation software, train overturning stability calculation software under strong side winds, train dynamic marshalling monitoring software, plateau railway winds wireless transmission control software, plateau railway wind data processing analysis software, plateau railway real-time forecast wind analysis software.
     For the high reliability requirements of plateau railway operation under the bad weather, the system realizes the remote automatic monitor and control and fault status information auto storage, constructes the reliability plateau railway operation system including the strong wind monitoring and train traffic control system, ensuring all-weather and high-reliability operation.
     Since been opened uninterruptedly from July 2006 up to now, the strong wind monitoring and warning system and train traffic control system of the plateau railway are stable and reliable after two-year trial operation. It has directed stopping train or limiting speed many times, guaranteeing the train operation safety and transportation efficiency effectively, providing guarantee to the operation danger of Qinghai-Tibet Railway when comes across strong wind. The system not only provides an effective mean to guarantee the rail safety under the condition that the direction of strong wind is diversity and different to build break-wind walls along rail lines, but also lay an important foundation to solve all of the train operation safety problems in China.
引文
[1]Anderson, H. L. Investigation of the Forces on Bluff Bodies Near the Ground, M. Sc. dissertation, Department of Aeronautics, Imrperial College,1977
    [2]田红旗,杨明智、许平、高光军等.侧风作用下车辆空气动力性能风洞实验研究.中南大学,2006
    [3]Fujii T. Maeda T, Ishida H. Wind-induced Accidents of Train/Vehicles and Their Measure in Japan. Quarterly Report of Railway Technical Research Institute,1999, (1):50-55
    [4]Coleman, S.A., Baker, C. J., High Sided Road Vehicles in Crosswinds. Journal of wind Engineering and Industrial Aerodynamics,1990,36(2): 1383-1392
    [5]葛盛昌,尹永顺.新疆铁路风区列车安全运行标准现场试验研究.铁道技术监督,2006.39(4):9-11
    [6]前田达夫, 江慧.高速铁路的空气动力学现象与环境问题.变流技术与电力牵引,2000, (2):35-37
    [7]種本勝二, 鈴木実, 前田達夫.横風に对する車両の空力学的特性風洞試験.铁道缏研報告,1999,13(12):47-52.
    [8]今井俊昭.对铁道强风管制风速评定的探讨.铁道综研报告-环境防灾技术特集.1997,10
    [9]小野纯朗.提高列车速度的理论和实践.徐涌译.北京:中国铁道出版社,1992
    [10]Noritoshi Kobayashi, Makoto Shimamura. Study of a Strong Wind Warning System. JR EAST Technical Review.2003, (2):61-65
    [11]Quinn, A.D. An Investigation of the Wind-induced Rolling Moment on a Commercial Vehicle in the Atmospheric Boundary Layer. Proceedings of the Institution of Mechanical Engineers, Part D:Journal of Automobile Engineering,2007,21(11):1367-1379
    [12]Coleman, S.A. Experimental Study of the Aerodynamic Behavior of High Sided Lorries in Cross Winds. Journal of Wind Engineering and Industrial Aerodynamics,1994,54(3):401-429
    [13]Baker, C.J. Behaviour of Road Vehicles in Unsteady Cross Winds. Journal of Wind Engineering and Industrial Aerodynamics,1993,49(1):439-448
    [14]Baker, C.J. Assessment of Wind Tunnel Testing Techniques for Ground Vehicles in Cross Winds. Journal of Wind Engineering and Industrial Aerodynamics,1990,33(1):429-438
    [15]Baker, C.J. Wind Tunnel Tests to Obtain Train Aerodynamic Drag Coefficients. Journal of Wind Engineering and Industrial Aerodynamics,1991,38(1):23-28
    [16]Baker, C.J. High Sided Articulated Board Vehicles in Strong Cross Winds. Journal of Wind Engineering and Industrial Aerodynamics,1988,31(1): 67-85
    [17]Baker, C.J. Problems of Road Vehicles in Cross Winds. Highways and Transportation,1991,38(5):8-9
    [18]Brockie, N.J.W. Aerodynamic Drag of High Speed Trains. Journal of Wind Engineering and Industrial Aerodynamics,1990,34(3):273-290
    [19]Coleman, S.A. High Sided Road Vehicles in Cross Winds. Journal of Wind Engineering and Industrial Aerodynamics,1990,36(2):1383-1392
    [20]Coleman, S.A Reduction of Accident Risk for High Sided Road Vehicles in Cross Winds. Journal of Wind Engineering and Industrial Aerodynamics, 1992,44(4):2685-2695
    [21]Humphreys, N.D. Forces on Vehicles in Cross Winds from Moving Model Tests. Journal of Wind Engineering and Industrial Aerodynamics,1992,44(4): 2673-2684
    [22]Matschke G., Schulte-Werning B. Measures and Strategies to Minimize the Effect of Strong Cross Winds on High Speed Trains. Proceedings of WCRR World Congress of Railway Research, Florence, Italy, Vol. E,569-575, 1997
    [23]Uwe Hoppmann, Stefan Koenig, Thorsten Tielkes, Gerd Matschke. A short-term Strong Wind Prediction Model for Railway Application:Design and Verification. Journal of Wind Engineering and Industrial Aerodynamics,2002, 90(10):1127-1134
    [24]British Railway Group Standard. GM/RT2141. Resistance of RailwayVehicles to Oerturning in Gales. Derby:Safety & Standards Directorate,1994
    [25]熊小慧,梁习锋,高广军.兰州-新疆线强侧风作用下车辆的气动特性.中南大学学报(自然科学版),2006,37(6):1183-1189
    [26]尹永顺, 王厚雄等.兰新复线防风安全工程研究报告.乌鲁木齐铁路局,1994,2
    [27]中南大学.强侧风影响下车辆运行稳定性研究报告.中南大学,2003
    [28]刘凤华,加筋土式挡风墙优化研究.铁道工程学报,2006,(1):96-99
    [29]刘凤华.挡风墙气动外形及位置优化[硕士学位论文].中南大学,2006
    [30]中南大学.强侧风条件下车体表面压力分布现场测试.中南大学,2006
    [31]叶文军等.铁路沿线灾害性天气监测、预测、预警系统.新疆气象,2001,26(6):25-27
    [32]任建.青藏铁路客车的几点思考.铁道车辆,2003,41(10):4-8
    [33]邱道成.青藏铁路格拉段高原冻土站场设计的特点.冰川冻土,2003,25(S1):133-135
    [34]白虎志, 李栋梁,董安祥.青藏铁路沿线的大风特征及风压研究.冰川冻土.2005,27(1):111-116
    [35]白虎志,董安祥,李栋梁,等.青藏高原及青藏铁路沿线大风沙尘日数时空特征.高原气象,2005,24(3):311-315.
    [36]田红旗、梁习锋、许平、高广军、杨明智等.青藏高原铁路大风下行车安全保障系统研究报告.中南大学.2007.3
    [37]李燕飞, 梁习锋, 刘堂红.环境风对路堤上快运集装箱平车气动力性能影响.铁道科学与工程学报,2007,4(5):78-82
    [38]梁习锋, 熊小慧.4种车型横向气动性能分析与比较.中南大学学报(自然科学版),2006,37(3):607-612
    [39]何华,田红旗,熊小慧.横风作用下敞车的气动性能研究.中国铁道科学,2006,27(3):73-79
    [40]梁习锋,熊小慧, 易仕和.强侧风作用下棚车气动外形优化.国防科技大学学报,2006,28(2):26-30
    [41]梁习锋, 舒信伟.列车风挡对空气阻力影响的数值模拟研究.铁道学报,2003,25(1)34-37
    [42]高广军, 田红旗, 姚松, 刘堂红, 毕光红.兰新线强侧风对车辆倾覆稳定性的影响.铁道学报,2004,26(4):36-40
    [43]高广军, 田红旗,张健.横风对双层集装箱平车运行稳定性的影响.交通运输工程学报,2004,4(2):45-48
    [44]田红旗、许平、潘迪夫、刘辉、陈峰等.青藏铁路大风监测预警与行车指挥系统系统研建报告,2007.3
    [45]成盛.DCS、PLC与现场总线系统在电厂的应用发展.山西焦煤科.2008,7:72-74
    [46]康玮.基于.NET的DCS组态软件研究与设计.湖南大学硕士学位论文.2006.3
    [47]王吉峰.基于PLC与DCS的过程控制系统集成方案的设计与实施.山东大学硕士学位论文.2007.8
    [48]刘科.工业以太网实时通信技术及进展.工矿自动化.2005,6(3):53-55
    [49]周美娇,应启戛,彭杰.用于过程控制的工业以太网通信模型.仪器仪表学报.2005,8(8)增.495-497
    [50]杜品圣.工业以太网技术的介绍和比较.仪器仪表标准化与计量.2005.5:17-19
    [51]仲崇权.工业现场数据采集与工业以太网若干关键技术.大连理工大学硕士学位论文.2006.11
    [52]陈磊.从现场总线到工业以太网的实时性问题研究.浙江大学博士学位论文.2004.5
    [53]刘洪波.基于OPC规范的数据通信软件研究与实现.吉林大学硕士学位论文.2008.4
    [54]祝杰,沈春山,吴仲城,申飞.OPC技术在DCS数据访问中的应用.华中科技大学学报(自然科学版).2008.10(36)增刊:251-253
    [55]刘彬,程大章.面向过程控制的一种新技术——OPC数据访问标准.计算机工程.2000.10(10):127-129
    [56]土德康,苏宏业,褚健.基于O PC技术的先进控制软件设计与研究.化工自动化及仪表.2000.27(4):27-30
    [57]赵众,邹芳云,徐宁,孙康.OPC客户端程序开发及其在集散控制系统中的应用.化工自动化及仪表.2007,34(3):42-46
    [58]李国厚.OPC技术与控制系统集成.计算机自动测量与控制.2001.9(2):11-13
    [59]张国琼,陈雪波,董贵宏.工业控制软件互操作标准—OPC技术及应用.鞍山科技大学学报.2003.2(26):12-15
    [60]顾志刚.一类基于OPC的工业控制系统的研究.浙江工业大学信息工程学院硕士学位论文.2007.12
    [61]钟章队,李旭,蒋文怡等编著.铁路综合数字移动通信系统(GSM-R).中国 铁道出版社.
    [62]黄威,贾利民,钟彬.GSM-R数字移动通信系统及其应用.铁路计算机应用,2005(12)
    [63]韩斌杰.GSM原理及网络优化[M].北京:机械工业出版社,2002
    [64]邵世像,林纲.GSM移动通信网络优化[M].北京:人民邮电出版社,2002
    [65]廖胜.基于ARM和GPRS远程监控系统的研究.北京邮电大学硕士学位论文.2008.2
    [66]苏金拢.GPRS技术构成和发展.福建电脑.2005.12:16-18
    [67]邵远,何发昌,罗志增.多传感器信息融合浅析.申子学报.1994.5(5):73-78
    [68]王漩,李春升,周荫清.多传感器信息融合技术.北京航空航天大学学报.1994.10(4):402-406
    [69]肖斌.多传感器信息融合及其在工业中的应用.太原理工大学硕士学位论文.2008.5
    [70]周敏.城市交通流多源信息采集与融合方法的研究及应用.浙江工业大学硕士学位论文.2008.4
    [71]卜荣飞.基于多传感器融合的机器人嗅觉感知系统.河北工业大学硕士学位论文.2007.12
    [72]于淑香.关系数据库的查询优化技术.沙洲职业工学院学报.2006.8(3):17-19
    [73]肖捷,肖正新,袁华强.关系数据库查询优化策略的分析与应用.计算机与现代化.2006.11:116-118
    [74]彭华熔.空间数据全关系化存储的实现及其集成管理技术的研究.中南大学硕士学位论文.2005.5
    [75]何养育,韩慧莲.数据库系统概述.机械管理开发.2008.2(1):93-94
    [76]袁书宏.面向学生数据中心的数据集成平台的研究、设计及实现.浙江工业大学硕士学位论文.2006.5
    [77]Hoppmann Uwe, Koenig Stefan, Tielkes Thorsten.A short-term strong wind prediction model for railway application:design and verification. Journal of Wind Engineering and Industrial Aerodynamics,2002 (90):1127-1134.
    [78]Xie Lian, Bao Shaowu, Pietrafesa Leonard J. A real-time hurricane surface wind forecasting model:Formulation and verification, Monthly Weather Review,2002,134(5):1355-1370.
    [79]Milligan Michael, Schwartz Marc, Wan Yih-Huei. Statistical wind power forecasting for U.S. Wind farms,84th American Meteorological Society (AMS) Annual Meeting,2004:3637-3644.
    [80]Zaphiropoulos Yiorgos, Dellaportas Petros, Morfiadakis Evangelos. Prediction of wind speed and direction at a potential site, Wind Engineering, 1999,23 (3):167-175.
    [81]Li Shuhui. Wind Power Prediction Using Recurrent Multilayer Perceptron Neural Networks,2003 IEEE Power Engineering Society General Meeting, Conference Proceedings,2003 (4):2325-2330.
    [82]El-Fouly T.H.M, El-Saadany E.F, Salama M.M.A. Grey predictor for wind energy conversion systems output power prediction, IEEE Transactions on Power Systems.2006,21(3):1450.
    [83]Basu S, Satheesan K, Sarkar, A. Ocean surface wind prediction in the north Indian Ocean from in situ and satellite observations using genetic algorithm, Geophysical Research Letters.2005,32 (24):5.
    [84]Rife D.L, Davis C.A, Yubao Liu. Predictability of low-level winds by mesoscale meteorological models, Monthly Weather Review.2004,132 (11): 2553-2569.
    [85]吴国肠,肖洋,翁莎莎.风电场短期风速预测探讨.电力自动化设备,2005,(8):21-24.
    [86]丁明,张立军,吴义纯.基于时间序列分析的风电场风速预测模型.电力自动化设备,2005,25(8):32-34.
    [87]肖永山,王维庆,霍晓萍.基于神经网络的风电场风速时间序列预测研究.节能技术,2007,25(2):106-109.
    [88]杨秀媛,肖洋,陈树勇.风电场风速和发电功率预测研究.中国电机工程学报,2005,25(11):1-5.
    [89]马静波,杨洪耕.自适应卡尔曼滤波在电力系统短期负荷预测中的应用.电网技术,2005,29(1):75-79.
    [90]谢宏,陈志业,牛东晓,等.基于小波分解与气象因素影响的电力系统日负荷预测模型研究.中国电机工程学报,2001,21(5):5-10.
    [91]李天云,刘自发.电力系统负荷的混沌特性及预测.中国电机工程学报,2000,20(11):36-40.
    [92]邰能灵,候志俭,李涛,等.基于小波分析的电力系统短期负荷预测方法.中国电机工程学报,2003,23(1):45-50.
    [93]耿波,王君杰,张谢东.桥梁技术状况预测的灰色马尔可夫链模型研究.武汉理工大学学报(交通科学与工程版),2007,31(1):107-110.
    [94]姜可宇,蔡志明,陆振波.基于RBF神经网络的混沌时间序列前后向联合预测模型.武汉理工大学学报(交通科学与工程版),2007,31(2):259-261.
    [95]黄宜军,邬长安.基于自适应多小波网络预测模型的飞控系统故障诊断仿真研究.系统仿真学报,2008,5(3):1270-1273.
    [96]李瑞莹,康锐.基于神经网络的故障率预测方法.航空学报,2008,29(2):357-364.
    [97]李红启,刘凯.基于Rough Set理论的铁路货运量预测.铁道学报,2004,26(3):1-7.
    [98]李红启,刘凯.基于分形理论的铁路货运量分析.铁道学报,2003,25(3):19-24.
    [99]张诚,周湘峰.基于灰色预测-马尔可夫链-定性分析的铁路货运量预测.铁道学报,2007,29(5):15-21.
    [100]张树京,齐立心.时间序列分析简明教程[M].北京:清华大学出版社,北方交通大学出版社2003.
    [101]杨叔子,吴雅.时间序列分析的工程应用[M].武汉:华中理工大学出版社,1992.
    [102]王志贤.最优状态估计和系统辨识[M].西安:西北工业大学出版社,2004.
    [103][美]Lonnie C.Ludeman.邱天爽,李婷,毕英伟等译.随机过程——滤波、估计和检测[M]北京:电子工业出版社,2005.
    [104]朱涛.TMIS综合调度管理信息系统.计算机应用.2005.7(14):15-18
    [105]江冬,苗慧,伯克明.TMIS车站运输统计系统的设计与实现.计算机应用.2004.3(13):14-17
    [106]孙远运.TMIS总体架构设计研究.计算机应用.2005.7(14):11-14
    [107]谢肇桐.列车调度指挥系统TDCS.铁道知识.2005.4:32-33
    [108]冯皓.探讨TDCS的发展.铁路通信信号工程技术.2008.5(2):50-53
    [109]吕品,夏红霞,李明.异构数据库互操作平台的开发研究.武汉理工大学学报·信息与管理工程版.2003.2(1):35-38
    [110]张伟昆,王大栩.异构型数据库互连技术研究与实现.交通与计算机.2002.4(20):33-37
    [111]陈万盛.异构数据库移植及其同步问题研究.昆明理工大学硕士学位论文.2008.1
    [112]郑丽丽.基于XML的异构数据交换模型的研究.山东师范大学硕士学位论文.2008.4
    [113]周丹, 田红旗, 鲁寨军.大风对路堤上运行的客运列车气动性能的影响.交通运输工程学报,2007,7(4):7-10
    [114]田红旗,许平.列车交会压力波与运行速度的关系.中国铁道科学,2006,27(6):64-67
    [115]许平, 田红旗, 姚曙光.流线型列车头部外形设计方法.中国铁道科学,2007,27(1):33-35
    [116]田红旗, 周丹, 许平.列车空气动力性能与流线型头部外形.中国铁道科学,2006,27(3):47-55
    [117]周丹, 田红旗, 杨明智.强侧风作用下不同类型铁路货车在青藏线路堤上运行时的气动性能比较.铁道学报,2007,29(5):32-37
    [118]熊小惠.横风作用下青藏铁路列车横断面气动外形优化研究[硕士论文].中南大学,2004
    [119]田红旗、梁习锋、许平、高广军、杨明智等.青藏铁路大风对行车安全影响研究报告.中南大学.2007.3
    [120]苏权.基于_NET技术的人事信息综合系统设计与实现.南京理工大学工程硕士学位论文.2007.9
    [121]张金标,周剑.基于.NET平台的广播发射台实时监控系统.中国传媒大学学报自然科学版.2006.3(1):66-70
    [122]杨波.基于Web Service异构数据集成技术的研究.河北工业大学硕士学位论文.2007.12
    [123]李卫东,单新建.基于Web Services的多源异构空间信息集成框架.微计算机信息.2008.7(3):14-17
    [124]窦则欣.基于SAPI引擎的文本编辑工具中语音命令的应用研究.沈阳工业大学硕士学位论文.2007.1
    [125]傅蓉.文本_可视语音合成系统的研究及实现.新疆大学硕士学位论文.2005.6
    [126]郭立力,赵春江.高效FTP搜索引擎的设计与实现.华南理工大学学报(自然科学版).2009.1(1):135-140
    [127]孙韩林,金跃辉,高雪松,张健.FTP协议的测试及分析.计算机工程.2008.12(23):133-136
    [128]叶水仙,林国忠.基于XML远程数据交换的实现.科学技术与工程.2006.12(6):3874-3877

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700