Study On Key Technology Of Pipeline Crack Detection Based On Eddy Current Effect

As an important tool for energy transportation,oil and gas pipelines are widely used in industries such as petroleum,chemical industry,energy and environmental protection,and are an important carrier for realizing the close connection between oil and gas resources and the market.Cracks are a major hidden danger in pipeline transportation.Once not detected in time,it is easy to lead to safety accidents.Therefore,regular inspection and maintenance of pipelines is of great significance to effectively prevent accidents and ensure the safe and stable operation of pipelines.In this paper,based on the investigation of eddy current detection technology and pipeline defect identification and inversion technology at home and abroad,the research on the detection and quantitative identification method of oil and gas pipeline cracks based on eddy current effect is carried out.The main research contents are as follows:(1)The principle and simulation research of pipeline crack eddy current detection.Starting from the magnetization mechanism of ferromagnetic materials,the principle of eddy current detection of pipeline cracks is explored,a simplified three-dimensional finite element simulation model is established,and the influence of lift-off height,excitation signal parameters,excitation coil parameters,and artificial defect size parameters on the magnetic field signal is explored.(2)According to the actual working conditions,the overall scheme of the pipeline crack eddy current detector is designed,including the inner detector skeleton,data acquisition system,probe support mechanism,mileage wheel,detection probe and the overall arrangement scheme design of the probe.For φ273 pipelines,the passability of the inner detector at the 1.5D×90° elbow was studied,and the rationality of the structure was verified,the technical indicators of the eddy current crack detection probe were proposed,and different single detection modules and pipeline circumferential probe arrangements were compared.Combined with the axial and circumferential detection accuracy,select the optimal probe arrangement scheme.(3)An eddy current testing system for pipeline cracks was built,the geometric size of the testing probe was optimized,and the influence of excitation current amplitude,defect size,crack angle,and the relative position of the defect and the probe on the detection effect was explored.Through the simulation and experimental results,the characteristic parameters and training parameters of the pipeline defect response signal are selected.(4)Research on detection signal processing and quantitative identification of defects.Perform wavelet threshold noise reduction processing on the detection signal,compare the wavelet noise reduction effects of dmey,haar and db3,and combine the signal-to-noise ratio and root mean square error to determine the optimal noise reduction method is haar wavelet soft SURE threshold noise reduction,through simulation According to the experimental results,the characteristic parameters and training parameters of pipeline defects are selected,the BP neural network is used to quantitatively identify the defect size,and the sparrow search algorithm is used to optimize the BP neural network to improve the quantitative identification accuracy.The identification accuracy of the intelligent algorithm and the traditional algorithm is compared and analyzed.