基于GIS的地形起伏地区天然气管道路径寻优
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摘要
针对以往二维平面条件下确定天然气管道最优路径难以符合真实环境的情况,利用GIS软件Global Mapper提取高分辨率离散化三维地形数据,建立DEM数字高程模型(Digital Elevation Model,DEM)。基于DEM模型,以天然气管道长度最短为评价指标,管道弹性敷设曲率半径为约束条件,建立地形起伏地区管道路径寻优模型,采用改进的Dijkstra算法(A~*算法),应用启发式搜索方式,求解两点间最优的曲面路径。通过实际地形模拟分析表明,基于Global Mapper建立DEM数字高程模型工作量小、精度高,能够有效模拟地形的真实情况;A~*算法具有良好的全局收敛性和计算鲁棒性,适用于管道路径寻优模型的求解,能够有效缩短管道总长度,降低路径的起伏程度。
Path optimization of natural gas pipeline based on two-dimensional plane can hardly reflect the actual environment. In this paper, high-resolution discrete 3D terrain data was extracted using Global Mapper of GIS software and the Digital Elevation Model(DEM) was established. Based on the DEM, the path optimization model for the pipelines in hilly areas was established with the minimum length of natural gas pipeline as the evaluation index and the curvature radius of elastic installation as the constraint. Then the optimal surface path between two points was solved by the modified Dijkstra algorithm(A~* algorithm) in the mode of heuristic search. Finally, it was applied to simulate the actual landform. It is indicated that the DEM based on Global Mapper has the advantages of small workload and high precision and it can be used as the simulated landform effectively. Besides, the A~* algorithm is better in global convergence and calculation robustness and applicable to the solution of pipeline path optimization model. By virtue of A~* algorithm, the total pipeline length and the path fluctuation degree can be decreased effectively.
Path optimization of natural gas pipeline based on two-dimensional plane can hardly reflect the actual environment. In this paper, high-resolution discrete 3D terrain data was extracted using Global Mapper of GIS software and the Digital Elevation Model(DEM) was established. Based on the DEM, the path optimization model for the pipelines in hilly areas was established with the minimum length of natural gas pipeline as the evaluation index and the curvature radius of elastic installation as the constraint. Then the optimal surface path between two points was solved by the modified Dijkstra algorithm(A~* algorithm) in the mode of heuristic search. Finally, it was applied to simulate the actual landform. It is indicated that the DEM based on Global Mapper has the advantages of small workload and high precision and it can be used as the simulated landform effectively. Besides, the A~* algorithm is better in global convergence and calculation robustness and applicable to the solution of pipeline path optimization model. By virtue of A~* algorithm, the total pipeline length and the path fluctuation degree can be decreased effectively.
引文
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[16]殷超.基于改进Dijkstra算法的最短路径搜索仿真[J].山东理工大学学报(自然科学版),2010,24(6):33-35.YIN C.Simulation of the shortest path search based on improved Dijkstra algorithm[J].Journal of Shandong University of Technology(Natural Science Edition),2010,24(6):33-35.
[17]吴宏超,刘检华,唐承统,等.基于改进A*算法的管路自动布局设计与优化方法[J].计算机集成制造系统,2016,22(4):946-953.WU H C,LIU J H,TANG C T,et al.Automatic pipe layout design and optimization method based on improved A*algorithm[J].Computer Integrated Manufacturing Systems,2016,22(4):946-953.
[18]单伟,孟正大.基于改进A*算法的平滑路径设计[J].东南大学学报(自然科学版),2010,40(1):156-161.SHAN W,MENG Z D.Smooth path design for mobile service robots based on improved A*algorithm[J].Journal of Southeast University(Natural Science Edition),2010,40(1):156-161.
[19]朱云鸿,袁一.基于改进A*算法的最优路径搜索[J].计算机技术与发展,2018(4):22-26.ZHU Y H,YUAN Y.An optimal path search based on the improved A*algorithm[J].Computer Technology and Development,2018(4):22-26.
[20]刘云翔,杜杰,张晴.基于路径优化的A*算法与Dijkstra算法的性能比较[J].现代电子技术,2017,40(13):182-186.LIU Y X,DU J,ZHANG Q.Performance comparison between A*algorithm and Dijkstra algorithm based on path optimization[J].Modern Electronics Technique,2017,40(13);182-186.
[2]周军,宫敬,李晓平.气体管道路径自动寻优[J].化工机械,2014,14(1):60-63.ZHOU J,GONG J,LI X P.Auto-optimized route for gas pipeline[J].Chemical Engineering&Machinery,2014,14(1):60-63.
[3]何国玺,梁永图,方利民,等.考虑三维地形及障碍的煤层气田集输系统布局优化[J].油气储运,2016,35(6):638-645.HE G X,LIANG Y T,FANG L M,et al.Layout optimization of gathering systems in CBM fields considering three dimensional terrains and obstacles[J].Oil&Gas Storage and Transportation,2016,35(6):638-645.
[4]甄宝军.考虑凸形障碍物的天然气集输管网系统规划研究[D].成都:西南石油学院,2005:37-46.ZHEN B J.The study of gas gathering pipe network system considering the convex obstacles[D].Chengdu:Southwest Petroleum Institute,2005:37-46.
[5]周军,李晓平,温凯,等.地形起伏条件下的枝状管网布局优化[J].油气田地面工程,2013,32(11):3-4.ZHOU J,LI X P,WEN K,et al.The layout optimization of dendritic pipeline network under the condition of terrain ups and downs[J].Oil-Gas Field Surface Engineering,2013,32(11):3-4.
[6]谢建华,刘春梅,井元伟.军事地图等高线的识别与提取[J].东北大学学报(自然科学版),2006,27(8):146-150.XIE J H,LIU C M,JING Y W.Identification and pick-up for contour line on military map[J].Journal of Northeastern University(Natural Science),2006,27(8):146-150.
[7]王建宇,滕树钦.一种基于等高线生成DEM的方法[J].计算机应用,2002,22(8):30-31.WANG J Y,TENG S Q.The method of making DEM based on contour line[J].Computer Applications,2002,22(8):30-31.
[8]呼雪梅,秦承志.地形信息对确定DEM适宜分辨率的影响[J].地理科学进展,2014,33(1):50-55.HU X M,QIN C Z.The effect of terrain information on the determination of the appropriate resolution of DEM[J].Progress in Geography,2014,33(1):50-55.
[9]刘学军,卢华兴,仁政,等.论DEM地形分析中的尺度问题[J].地理研究,2007,26(3):433-442.LIU X J,LU H X,REN Z,et al.Scale issues in digital terrain analysis and terrain modeling[J].Geographical Research,2007,26(3):433-442.
[10]汤国安,刘学军,房亮,等.DEM及数字地形分析中尺度问题研究综述[J].武汉大学学报(信息科学版),2006,31(12):1059-1066.TANG G A,LIU X J,FANG L,et al.A review on the scale issue in DEMs and digital terrain analysis[J].Geomatics and Information Science of Wuhan University,2006,31(12):1059-1066.
[11]宋晓猛,张建云,占车生,等.基于DEM的数字流域特征提取研究进展[J].地理科学进展,2013,32(1):31-40.SONG X M,ZHANG J Y,ZHAN C S,et al.Advances in digital watershed features extracting based on DEM[J].Progress in Geography,2013,32(1):31-40.
[12]李擎,谢四江,童新海,等.一种用于车辆最短路径规划的自适应遗传算法及其与Dijkstra和A*算法的比较[J].北京科技大学学报,2006,28(11):1082-1086.LI Q,XIE S J,TONG X H,et al.A self-adaptive genetic algorithm for the shortest path planning of vehicles and its comparison with Dijkstra and A*algorithms[J].Journal of University of Science and Technology Beijing,2006,28(11):1082-1086.
[13]SUN X X,KOENIG S,YEOH W.Generalized adaptive A*[C].New York:The International Joint Conference on Autonomous Agents and Multiagent Systems,2008:469-476.
[14]YAO J F,LIN C,XIE X B,et al.Path planning for virtual human motion using improved A*star algorithm[C].Tianjin:2010 Seventh International Conference on Information Technology,2010:1154-1158.
[15]SVEN K,MAXIM L.Real-time adaptive A*[C].New York:The International Joint Conference on Autonomous Agents and Multiagent Systems,2006:281-289.
[16]殷超.基于改进Dijkstra算法的最短路径搜索仿真[J].山东理工大学学报(自然科学版),2010,24(6):33-35.YIN C.Simulation of the shortest path search based on improved Dijkstra algorithm[J].Journal of Shandong University of Technology(Natural Science Edition),2010,24(6):33-35.
[17]吴宏超,刘检华,唐承统,等.基于改进A*算法的管路自动布局设计与优化方法[J].计算机集成制造系统,2016,22(4):946-953.WU H C,LIU J H,TANG C T,et al.Automatic pipe layout design and optimization method based on improved A*algorithm[J].Computer Integrated Manufacturing Systems,2016,22(4):946-953.
[18]单伟,孟正大.基于改进A*算法的平滑路径设计[J].东南大学学报(自然科学版),2010,40(1):156-161.SHAN W,MENG Z D.Smooth path design for mobile service robots based on improved A*algorithm[J].Journal of Southeast University(Natural Science Edition),2010,40(1):156-161.
[19]朱云鸿,袁一.基于改进A*算法的最优路径搜索[J].计算机技术与发展,2018(4):22-26.ZHU Y H,YUAN Y.An optimal path search based on the improved A*algorithm[J].Computer Technology and Development,2018(4):22-26.
[20]刘云翔,杜杰,张晴.基于路径优化的A*算法与Dijkstra算法的性能比较[J].现代电子技术,2017,40(13):182-186.LIU Y X,DU J,ZHANG Q.Performance comparison between A*algorithm and Dijkstra algorithm based on path optimization[J].Modern Electronics Technique,2017,40(13);182-186.