Experimental Study of Interference Factors and Finite Element Simulation on Oil-Gas Pipeline Magnetic Flux Leakage Density


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Some methods of enhancing oil-gas pipeline magnetic flux leakage (MFL) detection technique are introduced in the paper. Some man-made defects or imperfections on the pipe surface are detected via the axial magnetization inspection vehicle along the pipeline. The magnetic dipole model of corrosion defect is stated and the important interference factors on magnetic flux leakage are analyzed. Finite element method is used to analyze and simulate normal defects on pipe surface, which can attribute to get natural defect MFL signal. The influence of benign pipeline artifacts (valves, welds, tees, flanges, etc.), pipe material and pipe wall, vehicle velocity, defect dimensions and interaction among defects, and so on are studied in detail. The magnetic flux leakage contour images or indication extraction maps are given and presented. These interference factors are compensated and solved. These approaches and results applied in the paper are contributed to the feature extraction and indication of pipeline abnormality. The results suggest that these approaches and conclusions are significantly effective for the pipeline magnetic flux leakage inspection.



Advanced Materials Research (Volumes 26-28)

Edited by:

Young Won Chang, Nack J. Kim and Chong Soo Lee




J. Qi "Experimental Study of Interference Factors and Finite Element Simulation on Oil-Gas Pipeline Magnetic Flux Leakage Density", Advanced Materials Research, Vols. 26-28, pp. 1255-1260, 2007

Online since:

October 2007





[1] Sunho Yang, Finite element modeling of current perturbation method of nondestructive evaluation application, dissertation for degree of Doctor of Philosophy, Iowa State University, 2000. Fig. 6 MFL density map of different roundness from the same defect on pipe surface Fig. 7 MFL map and contour plot of pits aligned 300 to their axes.

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DOI: 10.1016/j.sna.2005.07.013

[3] Sun Xiangjun, Cao Lixin, Liu Fengshan, Feature Matching Based on Corner Affine Invariant, Journal of image and graphics, 2004, 9(5): 589-593.

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