MFL Detection Defect Reconstruction of Pipeline Based on Conjugate Gradient Methods

Li Jian Yang; Xiao Sun; Song Wei Gao

doi:10.4028/www.scientific.net/AMR.490-495.1066

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 490-495MFL Detection Defect Reconstruction of Pipeline...

MFL Detection Defect Reconstruction of Pipeline Based on Conjugate Gradient Methods

Abstract:

For the problem of MFL (magnetic flux leakage) inner detection signal reconstruction for pipeline, a method based on the FR conjugate gradient iterative was introduced to solve the inverse problem of electromagnetic field. The physical model of magnetic flux leakage inner detection in pipeline had been established by the finite element analysis software named ANSYS. 90 groups of different parameters of defects had been simulated in MFL. Fundamental function had been found by fitting curve. FR conjugate gradient iterative had been programmed by MATLAB in order to solve nonlinear equations. Comparing with Newton, conjugate gradient can get reconstruction defect parameter more accurately and better reconstruction results.

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Periodical:

Advanced Materials Research (Volumes 490-495)

Pages:

1066-1070

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.490-495.1066

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Online since:

March 2012

Authors:

Li Jian Yang, Xiao Sun, Song Wei Gao

Keywords:

Conjugate Gradient, Defect Reconstruction, Finite Element (FE) Simulation, Iterative Method, MFL Detection

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References

[1] Wenhua HAN, Peiwen QUE and Wei LIANG: The application of an improved genetic local search algorithm to MFL inverse problem. JOURNAL OF SHANG HAI JIAO TONG UNIVERSITY Vol. 41 (2007), pp.751-754.

DOI: 10.1109/icit.2005.1600861

Google Scholar

[2] Fengzhu JI, Changlong WANG and Siyang LIANG, et al: 2D defect reconstruction of pipeline from magnetic flux leakage signals based on LS-SVM. Journal of Southwest Petroleum University Vol. 29 (2007), pp.134-136.

Google Scholar

[3] Ramuhalli P, Udpa L and Udpa S S: Neural network-based in version algorithms in magnetic flux leakage nondestructive evaluation. Journal of Applied Physics Vol. 93(2003), pp.8274-8276.

DOI: 10.1063/1.1558693

Google Scholar

[4] Jinkui LIU, Kairong WANG and Li ZHENG: Modified FR conjugate gradient method and its global convergence. Guangxi Sciences Vol. 15 (2008), pp.383-385.

Google Scholar

[5] Xuewu DU, Boshun HAN and Liansheng ZHANG: Global Convergence of a Class of Unconstrained Minimization Methods Including the FR Method. OR TRANSACTIONS Vol. 8 (2004), pp.1-9.

Google Scholar

[6] Haifeng LIU, Xiuyan WANG and Renyang HE, et al: Study on simulation and experiment of magnetic flux leakage inspection for inner pipeline. Transducer and Microsystem Technologies Vol. 28 (2009), pp.61-64.

Google Scholar

[7] Feng REN, Xiaolei SHI: Building and validation performance fitted equations establishment of rolling piston type rotary compressor. Refrigeration and air-conditioning Vol. 9 (2009), pp.50-53.

Google Scholar