方威伦, 刘啸奔, 张宏, 陈朋超, 李睿, 赵晓明. 基于IMU数据的冻土区管道融沉风险段识别方法[J]. 油气储运, 2022, 41(3): 288-294. DOI: 10.6047/j.issn.1000-8241.2022.03.006
引用本文: 方威伦, 刘啸奔, 张宏, 陈朋超, 李睿, 赵晓明. 基于IMU数据的冻土区管道融沉风险段识别方法[J]. 油气储运, 2022, 41(3): 288-294. DOI: 10.6047/j.issn.1000-8241.2022.03.006
FANG Weilun, LIU Xiaoben, ZHANG Hong, CHEN Pengchao, LI Rui, ZHAO Xiaoming. Identification method for thaw settlement segments of pipelines in permafrost regions based on IMU data[J]. Oil & Gas Storage and Transportation, 2022, 41(3): 288-294. DOI: 10.6047/j.issn.1000-8241.2022.03.006
Citation: FANG Weilun, LIU Xiaoben, ZHANG Hong, CHEN Pengchao, LI Rui, ZHAO Xiaoming. Identification method for thaw settlement segments of pipelines in permafrost regions based on IMU data[J]. Oil & Gas Storage and Transportation, 2022, 41(3): 288-294. DOI: 10.6047/j.issn.1000-8241.2022.03.006

基于IMU数据的冻土区管道融沉风险段识别方法

Identification method for thaw settlement segments of pipelines in permafrost regions based on IMU data

  • 摘要: 惯性测量单元(Inertial Measurement Unit, IMU)可检测得到管道全线的弯曲应变海量数据, 但目前缺乏高效利用IMU数据进行管道定量评价的方法。为此, 提出一种基于IMU应变检测数据的冻土区融沉风险段管道识别方法, 其主要包括IMU应变数据预处理方法, 即数据对齐和弯头、凹陷、三通等非融沉段大应变特征识别方法, 以及通过预设识别阈值和待查异常管段建立的地质灾害段快速定位方法。采用该识别方法对漠大一线冻土区管道2013—2018年的IMU检测数据进行了识别分析, 识别结果与几何检测数据吻合较好。在此基础上, 统计了该冻土区管道不同区域的异常管段分布情况, 结果表明: 季节冻土区较多年冻土区地质变化点更多, 但变化较小。该研究为地质灾害地段管道的完整性评价提供了定量数据, 能够用于解决目前管道外部载荷无法确定的技术瓶颈, 是管道完整性评价技术发展的重要方向。

     

    Abstract: Massive data of bending strain along pipelines can be detected by the Inertial Measurement Unit(IMU), but there is no effective method available for the quantitative evaluation of pipelines with the IMU data so far. To address this issue, an identification method was proposed for thaw settlement segments of pipelines in permafrost zones based on IMU strain data. The method mainly includes the pre-processing method of IMU strain data, i.e., the data alignment method, the identification method of large strain characteristics of the non-thaw settlement pipeline segments, such as bends, dents and tees, and the quick positioning method of geological disaster pipeline segments determined by presetting the identification threshold and the abnormal pipeline segments to be inspected. Thus, the IMU detection data of the First Mohe-Daqing Pipeline in the permafrost region during 2013 to 2018 were identified and analyzed, and the identification results were in good agreement with the geometric inspection data. On that basis, a statistical analysis was made to study the distribution of abnormal pipeline segments in various areas of this permafrost region. The results indicate that the seasonal frozen region has more geological change points than the permafrost region, but the change is small. Generally, quantitative data are provided through this research for the integrity assessment of pipelines in geological disaster areas, which could be used to solve the technical bottleneck of failure to determine the external load of pipelines at present. Hence, it is a significant new direction for the development of pipeline integrity assessment technology.

     

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