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[1]唐建华　姜琳　李志鹏　刘金海.管道漏磁内检测失效数据处理方法[J].油气储运,2020,39(10):1-06.[doi:10.6047/j.issn.1000-8241.2020.10.006]
　TANG Jianhua,JIANG Lin,LI Zhipeng,et al.Processing method for failure data inpipeline MFL inline inspection[J].Oil & Gas Storage and Transportation,2020,39(10):1-06.[doi:10.6047/j.issn.1000-8241.2020.10.006]
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管道漏磁内检测失效数据处理方法

《油气储运》[ISSN:1000-8241/CN:13-1093/TE] 卷: 39 期数: 2020年10期 页码: 1-06 栏目: 出版日期: 2020-11-25
Title:
Processing method for failure data inpipeline MFL inline inspection
作者:
唐建华　姜琳　李志鹏　刘金海
Author(s):
TANG Jianhua;  JIANG Lin;  LI Zhipeng;  LIU Jinhai
关键词:
管道; 漏磁检测; 失效数据; 缺失数据插补; 数据清洗
Keywords:
pipeline;  MFL inspection;  failure data;  missing datainterpolation;  data cleaning
分类号:
TE88
DOI:
10.6047/j.issn.1000-8241.2020.10.006
文献标志码:
A
摘要:
管道漏磁内检测数据的有效性对缺陷检测的准确性影响极大，为了尽可能避免失效数据的影
响，通过分析漏磁失效信号的特征，设计了漏磁失效数据的处理方法：针对过限失效、尖峰失效、连
续过平滑、单通道数据漂移、传感器抖动5 类失效数据，采用阈值超限法、邻域差分阈值法、信号区域
面积、局部过零率等完成失效数据的检测与剔除；利用近邻搜索算法（K-NearestNeighbor，KNN），
并通过支持向量回归算法（Support Vector Regression，SVR）降低训练集的冗余性，设计了一种将
KNN 与SVR 相结合的漏磁缺失数据插补方法，对缺失数据进行插补。结果表明：对于不同程度的
数据缺失情况，管道漏磁失效数据处理方法可以实现对漏磁缺失数据的精确插补，对实际工程中常
出现的失效数据处理具有借鉴作用。

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更新日期/Last Update: 2020-08-13