张晓琳, 青松铸, 周秀兰, 罗彦力, 文崭, 胡超, 安壮. 管道内检测数据坐标化技术[J]. 油气储运, 2021, 40(6): 692-698. DOI: 10.6047/j.issn.1000-8241.2021.06.013
引用本文: 张晓琳, 青松铸, 周秀兰, 罗彦力, 文崭, 胡超, 安壮. 管道内检测数据坐标化技术[J]. 油气储运, 2021, 40(6): 692-698. DOI: 10.6047/j.issn.1000-8241.2021.06.013
ZHANG Xiaolin, QING Songzhu, ZHOU Xiulan, LUO Yanli, WEN Zhan, HU Chao, AN Zhuang. Data coordinate technology of pipeline in-line inspection[J]. Oil & Gas Storage and Transportation, 2021, 40(6): 692-698. DOI: 10.6047/j.issn.1000-8241.2021.06.013
Citation: ZHANG Xiaolin, QING Songzhu, ZHOU Xiulan, LUO Yanli, WEN Zhan, HU Chao, AN Zhuang. Data coordinate technology of pipeline in-line inspection[J]. Oil & Gas Storage and Transportation, 2021, 40(6): 692-698. DOI: 10.6047/j.issn.1000-8241.2021.06.013

管道内检测数据坐标化技术

Data coordinate technology of pipeline in-line inspection

  • 摘要: 目前,管道内检测数据均以里程作为管道缺陷点、异常点及特征点的定位基准,不利于缺陷修复及内检测数据的深度利用。为解决这一问题,提出由中心线测量实现内检测数据坐标化的技术流程,建立了根据中心线测量计算管道长度、弯头方向及曲率半径的数学算法模型,制定了中心线与内检测特征点的对齐拟合方法,并确定了拟合点的选取原则。现场开挖验证表明,该技术的平均误差为0.37m,是可行有效的。内检测数据坐标化可减少内检测缺陷修复工作量,节省修复费用;实现与管道外检测数据对齐,开展管道缺陷的成因、发展趋势、腐蚀活性等的深入分析,为管道数据整合提供技术支持。

     

    Abstract: At present, mileage is used as the location datum of pipeline defects, anomalies and feature points, which is not conducive to defect repair and deep utilization of in-line inspection data. Therefore, the technical process of coordinated in-line inspection data by center line measurement is put forward to solve this problem. The mathematical algorithm model of calculating pipeline length, elbow direction and curvature radius by center line measurement is established, the alignment fitting method of center line and in-line inspection feature points is studied and established, and the selection principle of fitting points is established. The excavation test shows that the average deviation of the technology is 0.37 m, and it is confirmed that the method is effective. Through the coordinated work of in-line inspection data, the workload and cost of repairing can be reduced, the cause, development trend and corrosion activity of pipeline defects can be analyzed in depth by aligning with external inspection data of pipeline, providing technical support for integration of pipeline data.

     

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