船舶智能化研究现状与展望
|
摘要
船舶智能化是在综合传感、通信、信息、计算机等多种先进技术的基础上,结合船舶具体应用环境,构建基于大数据、信息物理系统和物联网等特征的智能系统,使船舶航行、管理与服务更高效、更低耗、更安全和更环保。文章从大数据、信息物理系统、物联网三个方面介绍了船舶智能化的主要特征,从船舶智能航行和船舶智能管理与服务两个方面分析了船舶领域智能化的现状和展望。在船舶智能航行方面,探讨了综合船桥系统和无人驾驶的发展方向;在船舶智能管理与服务方面,分析了水路ITS、交通流理论和数据分析方法的最新发展,并提出了基于可视分析解决船舶管理大数据处理的流程。
Based on many advanced technologies, such as sensing, communication, information and computer and so on, ship intelligence structures an intelligent system possessing the characteristics of big data, cyber-physical systems(CPS) and internet of things(IOT) in consideration of specific application environment. The ship intelligence can make ship more efficient, lower consumption, safer and greener. In this paper, intelligence features including big data, CPS, IOT are presented. Review and prospect of ship intelligence are described from two aspects that are intelligent navigation, intelligent management and services. For intelligent navigation, an Integrated Bridge System(IBS) and unmanned driving technologies are introduced. For intelligent management and services, the latest developments of waterway ITS(intelligent transportation system), vessel traffic flow and data analysis method are introduced and a procedure of processing ship management big data based on visual analysis is proposed.
Based on many advanced technologies, such as sensing, communication, information and computer and so on, ship intelligence structures an intelligent system possessing the characteristics of big data, cyber-physical systems(CPS) and internet of things(IOT) in consideration of specific application environment. The ship intelligence can make ship more efficient, lower consumption, safer and greener. In this paper, intelligence features including big data, CPS, IOT are presented. Review and prospect of ship intelligence are described from two aspects that are intelligent navigation, intelligent management and services. For intelligent navigation, an Integrated Bridge System(IBS) and unmanned driving technologies are introduced. For intelligent management and services, the latest developments of waterway ITS(intelligent transportation system), vessel traffic flow and data analysis method are introduced and a procedure of processing ship management big data based on visual analysis is proposed.
引文
[1]柳晨光,初秀民,吴青,等.USV发展现状及展望[J].中国造船,2014,55(4):194-205.
[2]中国科技网.无人驾驶船舶:来日可期10年内将在全球航行[EB/OL].[2014-08-29].http://www.wokeji.com/military/3/201408/t20140829_804956.shtml.
[3]戚群,于涛.船舶交通管理系统(VTS)发展概况[J].中国无线电,2013(4):36-38.
[4]殷缶,梅深.长江电子航道图正式投用[J].水道港口,2015(1):64-64.
[5]严忠贞,严新平,马枫,等.绿色长江航运智能化信息服务系统及其关键技术研究[J].交通信息与安全,2010,28(6):76-81.
[6]李文然,曹文胜.基于物联网的智能化船舶签证系统[J].交通建设与管理,2014(6):184-187.
[7]石勇,陈懿冰.大数据技术在金融行业的应用及未来展望[J].金融电子化,2014(7):22-23.
[8]周光华,辛英,张雅洁,等.医疗卫生领域大数据应用探讨[J].中国卫生信息管理,2013(4):296-300.
[9]张引,陈敏,廖小飞.大数据应用的现状与展望[J].计算机研究与发展,2013,27(2):142-144.
[10]任磊,杜一,马帅,等.大数据可视分析综述[J].软件学报,2014,25(9):1909-1936.
[11]Hogarth R M,Soyer E.Using Simulated Experience to Make Sense of Big Data[J].MIT Sloan Management Review,2015,56(2):49-54.
[12]Lee EA.Cyber Physical Systems:Design Challenges[C]//Proceedings of International Symposium on Object Oriented Real-Time Distributed Computing.Orlando:IEEE,2008:363-369.
[13]罗俊海,肖志辉,仲昌平.信息物理系统的发展趋势分析[J].电信科学,2012,28(2):127-132.
[14]王中杰,谢璐璐.信息物理融合系统研究综述[J].自动化学报,2011,37(10):1157-1166.
[15]李仁发,谢勇,李蕊,等.信息—物理融合系统若干关键问题综述[J].计算机研究与发展,2012(6):1149-1161.
[16]Abdelzaher T.Research Challenges in Distributed Cyber-physical Systems[C]//Proceedings of International Conference on Embedded and Ubiquitous Computing.Shanghai:IEEE.2008.
[17]李光正,王涛,张国勇.基于物联网体系的智能船舶设计[J].船舶工程,2012,34(6):59-62.
[18]曹芳平.物联网关键技术在内河航道的应用探讨[J].物联网技术,2013(4):76-78.
[19]Chen C M,Yu L J,Ling P L,et al.The Architecture of IOT Smart Service System of Ocean Fishing Vessel and Its Application Based on Petri Net[J].Applied Mechanics and Materials,2013,385:1771-1775.
[20]Zhuang Y,Song S.Use of Internet of Things for Ship Management of Inland Rivers[C]//Proceedings of ICTIS2013:Improving Multimodal Transportation SystemsInformation,Safety,and Integration.Wuhan:ASCE.2013.
[21]董耀华,孙伟,董丽华,等.我国内河“船联网”建设研究[J].水运工程,2012(8):145-149.
[22]郑荣才,杨功流,李滋刚,等.综合船桥系统综述[J].中国惯性技术学报,2009,17(6):661-665.
[23]韩剑辉.综合船桥系统体系结构与部分关键技术研究[D].天津:天津大学,2009.
[24]曲全福,陈志刚,高洪宇.新型综合船桥系统[J].中国惯性技术学报,2011,19(3):325-328.
[25]林伟国,王立新.综合舰桥系统综述[J].船舶,2007(4):1-5.
[26]Belev B C.Information Capabilities of Integrated Bridge Systems[J].Journal of Navigation,2004,57(1):145-152.
[27]应士君,施朝健,陈锦标.基于多Agent的IBS故障诊断系统研究[C]//中国航海学会通信导航专业委员会2006年学术年会论文集.2006.
[28]潘泉,于昕,程咏梅,等.信息融合理论的基本方法与进展[J].自动化学报,2003,29(4):599-615.
[29]何非,何克清.大数据及其科学问题与方法的探讨[J].武汉大学学报:理学版,2014,60(1):1-12.
[30]Feng H.Cellular Automata Ship Traffic Flow Model Considering Integrated Bridge System[J].International Journal of u-and e-Service,Science and Technology,2013(6):121-132.
[31]Perera L P,Carvalho J P,Soares C G.Autonomous Guidance and Navigation Based on the COLREGs Rules and Regulations of Collision Avoidance[C]//Proceedings of the International Workshop“Advanced Ship Design for Pollution Prevention”.2009.
[32]徐婷婷.智能化船舶交通管理系统的体系结构研究[D].辽宁大连:大连海事大学,2008.
[33]Kao S L,Lee K T,Chang K Y,et al.A Fuzzy Logic Method for Collision Avoidance in Vessel Traffic Service[J].Journal of Navigation,2007,60(1):17-31.
[34]Wen C H,Hsu P Y,Wang C,et al.Identifying Smuggling Vessels with Artificial Neural Network and Logistics Regression in Criminal Intelligence Using Vessels Smuggling Case Data[M]//Pan J,Chen S,Nguyen N T.Intelligent Information and Database Systems.Berlin/Heidelberg:Springer,2012.
[35]Wu Y,Pelot R P,Hilliard C.The Influence of Weather Conditions on the Relative Incident rate of Fishing Vessels[J].Risk Analysis,2009,29(7):985-999.
[36]Wijaya W M,Nakamura Y.Predicting Ship Behavior Navigating through Heavily Trafficked Fairways by Analyzing AIS Data on Apache HBase[C]//Proceedings of International Symposium on Computing&Networking,Matsuyama:IEEE,2013.
[37]Li S.Analysis with Automatic Identification System Data of Vessel Traffic Characteristics in the Singapore Strait[J].Transportation Research Record:Journal of the Transportation Research Board,2014(2426):33-43.
[38]Schilk G,Seemann L.Use of ITS Technologies for Multimodal Transport Operations-river Information Services(RIS)Transport Logistics Services[J].ProcediaSocial and Behavioral Sciences,2012,48:622-631.
[39]European Commission.White Paper-Roadmap to a Single European Transport Area-Towards a Competitive and Resource Efficient Transport System[R].Brussels:European Commission,2011.
[40]刘静,关伟.交通流预测方法综述[J].公路交通科技,2004,21(3):82-85.
[41]Li M W,Han D F,Wang W.Vessel Traffic Flow Forecasting by RSVR with Chaotic Cloud Simulated Annealing Genetic Algorithm and KPCA[J].Neurocomputing,2015,157:243-255.
[42]刘敬贤,张涛,刘文.船舶交通流组合预测方法研究[J].中国航海,2009,32(3):80-84.
[43]Song C U,Lee Y S,Park Y S,et al.A Study on the Traffic Flow and Navigational Characteristics for the Ship's Routing of Po-Hang Port[J].Journal of Korean Navigation and Port Research,2005,29(10):821-826.
[44]Liu Z,Fu Y,Cong Y.The Simulation of Vessel Traffic Flow Based on Congruential Generator[C]//Proceedings of the International Conference on Remote Sensing,Environment and Transportation Engineering.2013.
[45]徐武雄,初秀民,陈先桥,等.桥区航道交通流仿真中船舶生成方法[J].系统仿真学报,2014,26(8):1644-1651.
[46]程学旗,靳小龙,王元卓,等.大数据系统和分析技术综述[J].软件学报,2014,25(9):1889-1908.
[47]刘祖源,张谢东.船舶操纵性能预报的人工神经网络方法[J].武汉交通科技大学学报,1997,21(1):1-5.
[48]姚杰,吴兆麟.船舶碰撞危险的自适应神经网络—模糊推理评价方法[J].中国航海,1999(1):14-19.
[49]孙延东.多源信息融合技术在VTS中的应用[D].辽宁大连:大连海事大学,2014.
[50]王鹏.船舶综合导航多源信息融合技术研究[D].江苏镇江:江苏科技大学,2014.
[51]夏荣菲,万隆君.基于知识融合的船舶能耗决策支持系统[J].船舶工程,2014(Z1):166-169.
[2]中国科技网.无人驾驶船舶:来日可期10年内将在全球航行[EB/OL].[2014-08-29].http://www.wokeji.com/military/3/201408/t20140829_804956.shtml.
[3]戚群,于涛.船舶交通管理系统(VTS)发展概况[J].中国无线电,2013(4):36-38.
[4]殷缶,梅深.长江电子航道图正式投用[J].水道港口,2015(1):64-64.
[5]严忠贞,严新平,马枫,等.绿色长江航运智能化信息服务系统及其关键技术研究[J].交通信息与安全,2010,28(6):76-81.
[6]李文然,曹文胜.基于物联网的智能化船舶签证系统[J].交通建设与管理,2014(6):184-187.
[7]石勇,陈懿冰.大数据技术在金融行业的应用及未来展望[J].金融电子化,2014(7):22-23.
[8]周光华,辛英,张雅洁,等.医疗卫生领域大数据应用探讨[J].中国卫生信息管理,2013(4):296-300.
[9]张引,陈敏,廖小飞.大数据应用的现状与展望[J].计算机研究与发展,2013,27(2):142-144.
[10]任磊,杜一,马帅,等.大数据可视分析综述[J].软件学报,2014,25(9):1909-1936.
[11]Hogarth R M,Soyer E.Using Simulated Experience to Make Sense of Big Data[J].MIT Sloan Management Review,2015,56(2):49-54.
[12]Lee EA.Cyber Physical Systems:Design Challenges[C]//Proceedings of International Symposium on Object Oriented Real-Time Distributed Computing.Orlando:IEEE,2008:363-369.
[13]罗俊海,肖志辉,仲昌平.信息物理系统的发展趋势分析[J].电信科学,2012,28(2):127-132.
[14]王中杰,谢璐璐.信息物理融合系统研究综述[J].自动化学报,2011,37(10):1157-1166.
[15]李仁发,谢勇,李蕊,等.信息—物理融合系统若干关键问题综述[J].计算机研究与发展,2012(6):1149-1161.
[16]Abdelzaher T.Research Challenges in Distributed Cyber-physical Systems[C]//Proceedings of International Conference on Embedded and Ubiquitous Computing.Shanghai:IEEE.2008.
[17]李光正,王涛,张国勇.基于物联网体系的智能船舶设计[J].船舶工程,2012,34(6):59-62.
[18]曹芳平.物联网关键技术在内河航道的应用探讨[J].物联网技术,2013(4):76-78.
[19]Chen C M,Yu L J,Ling P L,et al.The Architecture of IOT Smart Service System of Ocean Fishing Vessel and Its Application Based on Petri Net[J].Applied Mechanics and Materials,2013,385:1771-1775.
[20]Zhuang Y,Song S.Use of Internet of Things for Ship Management of Inland Rivers[C]//Proceedings of ICTIS2013:Improving Multimodal Transportation SystemsInformation,Safety,and Integration.Wuhan:ASCE.2013.
[21]董耀华,孙伟,董丽华,等.我国内河“船联网”建设研究[J].水运工程,2012(8):145-149.
[22]郑荣才,杨功流,李滋刚,等.综合船桥系统综述[J].中国惯性技术学报,2009,17(6):661-665.
[23]韩剑辉.综合船桥系统体系结构与部分关键技术研究[D].天津:天津大学,2009.
[24]曲全福,陈志刚,高洪宇.新型综合船桥系统[J].中国惯性技术学报,2011,19(3):325-328.
[25]林伟国,王立新.综合舰桥系统综述[J].船舶,2007(4):1-5.
[26]Belev B C.Information Capabilities of Integrated Bridge Systems[J].Journal of Navigation,2004,57(1):145-152.
[27]应士君,施朝健,陈锦标.基于多Agent的IBS故障诊断系统研究[C]//中国航海学会通信导航专业委员会2006年学术年会论文集.2006.
[28]潘泉,于昕,程咏梅,等.信息融合理论的基本方法与进展[J].自动化学报,2003,29(4):599-615.
[29]何非,何克清.大数据及其科学问题与方法的探讨[J].武汉大学学报:理学版,2014,60(1):1-12.
[30]Feng H.Cellular Automata Ship Traffic Flow Model Considering Integrated Bridge System[J].International Journal of u-and e-Service,Science and Technology,2013(6):121-132.
[31]Perera L P,Carvalho J P,Soares C G.Autonomous Guidance and Navigation Based on the COLREGs Rules and Regulations of Collision Avoidance[C]//Proceedings of the International Workshop“Advanced Ship Design for Pollution Prevention”.2009.
[32]徐婷婷.智能化船舶交通管理系统的体系结构研究[D].辽宁大连:大连海事大学,2008.
[33]Kao S L,Lee K T,Chang K Y,et al.A Fuzzy Logic Method for Collision Avoidance in Vessel Traffic Service[J].Journal of Navigation,2007,60(1):17-31.
[34]Wen C H,Hsu P Y,Wang C,et al.Identifying Smuggling Vessels with Artificial Neural Network and Logistics Regression in Criminal Intelligence Using Vessels Smuggling Case Data[M]//Pan J,Chen S,Nguyen N T.Intelligent Information and Database Systems.Berlin/Heidelberg:Springer,2012.
[35]Wu Y,Pelot R P,Hilliard C.The Influence of Weather Conditions on the Relative Incident rate of Fishing Vessels[J].Risk Analysis,2009,29(7):985-999.
[36]Wijaya W M,Nakamura Y.Predicting Ship Behavior Navigating through Heavily Trafficked Fairways by Analyzing AIS Data on Apache HBase[C]//Proceedings of International Symposium on Computing&Networking,Matsuyama:IEEE,2013.
[37]Li S.Analysis with Automatic Identification System Data of Vessel Traffic Characteristics in the Singapore Strait[J].Transportation Research Record:Journal of the Transportation Research Board,2014(2426):33-43.
[38]Schilk G,Seemann L.Use of ITS Technologies for Multimodal Transport Operations-river Information Services(RIS)Transport Logistics Services[J].ProcediaSocial and Behavioral Sciences,2012,48:622-631.
[39]European Commission.White Paper-Roadmap to a Single European Transport Area-Towards a Competitive and Resource Efficient Transport System[R].Brussels:European Commission,2011.
[40]刘静,关伟.交通流预测方法综述[J].公路交通科技,2004,21(3):82-85.
[41]Li M W,Han D F,Wang W.Vessel Traffic Flow Forecasting by RSVR with Chaotic Cloud Simulated Annealing Genetic Algorithm and KPCA[J].Neurocomputing,2015,157:243-255.
[42]刘敬贤,张涛,刘文.船舶交通流组合预测方法研究[J].中国航海,2009,32(3):80-84.
[43]Song C U,Lee Y S,Park Y S,et al.A Study on the Traffic Flow and Navigational Characteristics for the Ship's Routing of Po-Hang Port[J].Journal of Korean Navigation and Port Research,2005,29(10):821-826.
[44]Liu Z,Fu Y,Cong Y.The Simulation of Vessel Traffic Flow Based on Congruential Generator[C]//Proceedings of the International Conference on Remote Sensing,Environment and Transportation Engineering.2013.
[45]徐武雄,初秀民,陈先桥,等.桥区航道交通流仿真中船舶生成方法[J].系统仿真学报,2014,26(8):1644-1651.
[46]程学旗,靳小龙,王元卓,等.大数据系统和分析技术综述[J].软件学报,2014,25(9):1889-1908.
[47]刘祖源,张谢东.船舶操纵性能预报的人工神经网络方法[J].武汉交通科技大学学报,1997,21(1):1-5.
[48]姚杰,吴兆麟.船舶碰撞危险的自适应神经网络—模糊推理评价方法[J].中国航海,1999(1):14-19.
[49]孙延东.多源信息融合技术在VTS中的应用[D].辽宁大连:大连海事大学,2014.
[50]王鹏.船舶综合导航多源信息融合技术研究[D].江苏镇江:江苏科技大学,2014.
[51]夏荣菲,万隆君.基于知识融合的船舶能耗决策支持系统[J].船舶工程,2014(Z1):166-169.