摘要
针对传统油气管道数据监测方法检测准确度低的问题,设计基于大数据管理架构的油气管道数据监测分析模型。首先构建模型的整体架构,通过大数据支持收集和整理管道数据,对其进行预处理,确定关联排列行数和列数;引入布里渊传感技术,基于分布式光纤传感器和传感数据,通过光纤取代传统数百个传感点构成的数据生成回馈传感序列;通过计算模板和光纤反馈情况,生成距离数据,依靠散射点射谱关系距离,确定当前油气管道各处距离值,通过比对即可确定当前管道是否有弯曲情况,实现管道数据的监测。实验数据证明,基于大数据管理构架的油气管道监测分析模型在管道弯曲监测实验中,监测准确度更高,具有明显的监测优势。
In view of the low detection accuracy of traditional oil and gas pipeline data monitoring methods,the oil and gas pipeline data monitoring and analysis model based on big data management architecture is designed. In the design,the overall architecture of the model is built first,and then the big data is used to support the collecting and sorting out of the pipeline data,and the pipeline data are preprocessed to determine the number of lines and columns of the associated permutations.Brillouin sensing technology based on distributed fiber optic sensor and sensor data is introduced to replace the data composed of hundreds of traditional sensing points by optical fiber to generate feedback sensing sequence. The distance data is generated by calculating the template and the optical fiber feedback. The distance value of each place of the current oil and gas pipeline can be determined by the distance of scattering point spectral relation. By comparison of the two,whether the current pipeline is bent can be determined,so as to realize the monitoring of pipeline data. The experimental data proves that the oil and gas pipeline monitoring and analysis model based on the big data management framework has higher monitoring accuracy and obvious monitoring advantages in the pipeline bending monitoring experiments.
作者
孙啸
李双琴
谢锐
连江桥
郝靖仕
SUN Xiao;LI Shuangqin;XIE Rui;LIAN Jiangqiao;HAO Jingshi(School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China;Southwest Pipeline Branch Company of PetroChina Company Limited,Chengdu 610037,China;Beijing JAS Technical Service Co.,Ltd.,Beijing 100192,China)
出处
《现代电子技术》
北大核心
2020年第17期102-105,共4页
Modern Electronics Technique
关键词
大数据管理架构
油气管道
数据管理
收集整理
监测数据
监测效果对比
big data management framework
oil and gas pipeline
data management
collecting and sorting out
monitoring data
contrast of monitoring effect
