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基于弱磁信号的管道缺陷定量重构分析
Quantitative reconstruction analysis of pipeline defects based on weak magnetic signals
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- DOI:
- 10.3969/j.issn.1001-2206.2026.01.016
- 作者:
- 曹自力, 高庆伟
CAO Zili, GAO Qingwei
- 作者单位:
- 中国石油华北油田巴彦勘探开发分公司, 内蒙古巴彦淖尔 015000
Bayan Exploration and Development Branch, Huabei Oilfield of CNPC, Bayannur 015000, China
- 关键词:
- 弱磁检测; 磁感应强度; 缺陷参数; 重构模型; 正演模型
weak magnetic field detection;magnetic induction intensity;defect parameters;reconstruction model;forward model
- 摘要:
- 油气田集输管道因介质种类复杂、小管径较多等特点，常规无损检测方法适应性较差。基于磁偶极子理论构建弱磁信号正演模型，分析管道缺陷长度、深度、角度及提离高度对磁感应强度的影响，并对数据进行拉丁超立方抽样，建立BP-Kriging模型进行管道缺陷参数的定量重构，最终通过实例验证了该模型的有效性。结果显示，当缺陷长度增加时，磁感应强度轴向分量的峰值先上升后下降，而径向分量的峰谷幅值虽有所增加，但增长的速度逐渐减慢；随着缺陷深度的增加，轴向分量的峰值与径向分量的峰谷值均呈线性增长变化趋势；缺陷角度变化使磁场分量呈非线性变化；提离高度越小，检测信号越敏感；BP-Kriging模型预测结果中，缺陷长度和缺陷深度的决定系数均超0.9，缺陷角度的决定系数提升至0.89。工程验证表明，缺陷深度的预测稳定性略逊于缺陷长度和缺陷角度，模型整体预测误差处于可接受范围。研究结果可为弱磁信号的智能分析提供实际参考。
Due to the complex types of media in and the large number of small pipe diameters of gathering and transportation pipelines in oil and gas fields, conventional non-destructive testing methods have poor adaptability. Based on the magnetic dipole theory, a forward model of weak magnetic signals was constructed to analyze the influences of the length, depth, angle, and lifting height of pipeline defects on magnetic induction intensity. Latin hypercube sampling was conducted on the data, and the BP-Kriging model was established for the quantitative reconstruction of pipeline defect parameters. The validity of the model was verified through examples. The results show that when the defect length increases, the peak value of the axial component rises first and then falls, while the peak and valley values of the radial component increase somewhat, whereas the growth rate gradually slows down. With the increase of defect depth, both the peak value of the axial component and the peak and valley values of the radial component show a linear growth trend. The change in the defect angle causes the magnetic field component to change nonlinearly. The smaller the lifting height, the more sensitive the detection signal. In the prediction results of the BP-Kriging model, the determination coefficients of defect length and depth both exceed 0.9, and the determination coefficient of defect angle increases to 0.89. In engineering verification, the prediction stability of defect depth is slightly inferior to that of length and angle, and the overall prediction of the model is within an acceptable error range. The research results can provide practical references for the intelligent analysis of weak magnetic signals.