基于元胞自动机数学模型的瓦斯抽采管道漏点定位研究
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摘要
为了解决普通数学模型难以准确描述瓦斯抽采管道内流体的流动状态问题,提出了以元胞自动机模型为基础的瓦斯抽采管道漏点定位模型。根据元胞自动机在空间和时间上离散化的特性来演化管道流体在时空上的连续变化,将管径变化、管壁粗糙度、管构异件种类和数量以及温度等参数沿管道进行离散化,利用元胞自动机理论以及管道两端的信号对管道沿线压力和流量等参数变化进行预测,以判断泄漏的发生和漏点定位。通过实验验证,该方法能提高漏点定位精度。
In order to solve the problem that the ordinary mathematical model is difficult to accurately describe the flow state of fluid in the gas extraction pipeline,a model of leakage point positioning for the gas drainage pipeline based on the cellular automata model was presented. According to the discretization characteristics of cellular automata in space and time,the continuous change of pipeline fluid in space and time was evolved,and the parameters such as pipeline diameter change,pipeline wall roughness,types and quantities of pipeline structure irregular parts and temperature were discretized along the pipeline. Based on the cellular automata theory and the signals at both ends of the pipeline,the change of pressure and flow rate along the pipeline were predicted to determine the occurrence of leakage and the leakage point positioning. The experimental results showed that this method greatly improved the accuracy of leakage point positioning.
In order to solve the problem that the ordinary mathematical model is difficult to accurately describe the flow state of fluid in the gas extraction pipeline,a model of leakage point positioning for the gas drainage pipeline based on the cellular automata model was presented. According to the discretization characteristics of cellular automata in space and time,the continuous change of pipeline fluid in space and time was evolved,and the parameters such as pipeline diameter change,pipeline wall roughness,types and quantities of pipeline structure irregular parts and temperature were discretized along the pipeline. Based on the cellular automata theory and the signals at both ends of the pipeline,the change of pressure and flow rate along the pipeline were predicted to determine the occurrence of leakage and the leakage point positioning. The experimental results showed that this method greatly improved the accuracy of leakage point positioning.
引文
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[2]齐庆杰,祁云,张建国,等.综放工作面瓦斯抽采最优钻孔参数研究[J].中国安全生产科学技术,2018,14(6):33-36.QI Qingjie,QI Yun,ZHANG Jianguo,et al.Study on optimum borehole parameters for gas drainage in fully mechanized caving face[J].Journal of Safety Science and Technology,2018,14(6):33-36.
[3]温良秀,高科,刘剑.地面钻孔抽采对采空区瓦斯运移及自然发火的影响数值模拟研究[J].矿业安全与环保,2018,45(3):6-10.WEN Liangxiu,GAO Ke,LIU Jian.Numerical simulation study on influence of surface borehole extraction on gas migration and spontaneous combustion in goaf[J].Mining safety and Environmental Protection,2018,45(3):6-10.
[4]周正平.核电厂声学泄漏监测系统的设计和验证[J].核动力工程,2018,39(3):110-113.ZHOU Zhengping.Nuclear power plant design and verification of acoustic leakage monitoring system[J].Nuclear Power Engineering,2018,39(3):110-113.
[5]赵林,王纪强,侯墨语.煤矿管道泄漏监测系统设计[J].工矿自动化,2016,42(10):12-15.ZHAO Lin,WANG Jiqiang,HOU Moyu.Design of the monitoring system of coal mine pipeline leakage[J].Industry and Mine Automation,2016,42(10):12-15.
[6]陈华波,涂亚庆.输油管道泄漏监测方法综述[J].管道技术与设备,2000,37(1):38-41.CHEN Huabo,TU Yaqing.Review of oil pipeline leakage monitoring method[J].Pipeline Technique and Equipment,2000,37(1):38-41.
[7]李健,陈世利,黄新敬,等.长输油气管道泄漏监测与准实时检测技术综述[J].仪器仪表学报,2016,37(8):1747-1760.LI Jian,CHEN Shili,HUANG Xinjing,et al.Monitoring and review of quasi real time detection of oil and gas pipeline leakage[J].Chinese Journal of Scientific Instrument,2016,37(8):1747-1760.
[8]张红颖,杨旭伟,罗谦.基于元胞自动机的机场航班流建模与仿真[J].系统仿真学报,2018,30(8):2864-2874.ZHANG Hongying,YANG Xuwei,LUO Qian.Based on cellular automaton of flight flow modeling and simulation[J].Journal of System Simulation,2018,30(8):2864-2874.
[9]于明明,曾永年.顾及地类转换差异的城市空间扩展元胞自动机模型及应用研究[J].地球信息科学学报,2018,20(1):48-56.YU Mingming,ZENG Yongnian.Research on cellular automata model of urban spatial expansion and its application considering the differences of class conversion[J].Journal of Geo-Information Science,2018,20(1):48-56.
[10]张学良,谭惠丽,唐国宁,等.基于心脏腔式结构的心电图元胞自动机建模[J].物理学报,2017,66(20):18-26.ZHANG Xueliang,TAN Huili,TANG Guoning,et al.Modeling of ECG cellular automata based on cardiac cavity structure[J].Journal of Physics,2017,66(20):18-26.
[11]朱宁远,夏琴香,程秀全.基于元胞自动机的Haynes230动态再结晶组织演变[J].中南大学学报(自然科学版),2017,48(9):2316-2323.ZHU Ningyuan,XIA Qinxiang,CHENG Xiuquan.Dynamic recrystallization microstructure evolution of haynes 230 based on cellular automata[J].Journal of Central South University(Natural Science Edition),2017,48(9):2316-2323.
[12]李凯佳,俞锐刚,袁凌云.基于DNA-记忆元胞自动机与Hash函数的图像加密算法[J].计算机工程与设计,2017,38(2):470-477.LI Kaijia,YU Ruigang,YUAN Lingyun.Image encryption based on DNA-memory cellular automata and hash function[J].Computer Engineering and Design,2017,38(2):470-477.
[13]曾平安,郑智捷.利用变值编码展现元胞自动机的4类经典分类模式[J].计算机科学,2016,43(S1):139-141.ZENG Pingan,ZHENG Zhijie.Four classes of classical classification patterns of cellular automata using variable coding[J].Computer Science,2016,43(S1):139-141.
[14]于群,张敏,曹娜,等.基于模糊元胞自动机的电网连锁故障控制策略[J].电力自动化设备,2016,36(8):90-95.YU Qun,ZHANG Min,CAO Na,et al.Cascading fault control strategy of power grid based on fuzzy cellular automata[J].Electric Power Automation Equipment,2016,36(8):90-95.
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