Surface geometry reconstruction of corrosion defects of ferromagnetic materials product by the optimization by linear approximation

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Abstract

The paper describes a technique developed by the authors for reconstructing the shape and size of surface corrosion defects in products made of ferromagnetic materials based on measured components of the magnetic leakage field strength near the surface of the test object. The optimization problem of approximating the signal of a two-dimensional finite element model to the measured signal was solved by optimization using linear approximation with constraints. A method for approximating the defect shape using basis splines and a physical justification for choosing the reference points of spline interpolation are presented. The described technique was tested in a numerical experiment using a symmetrical defect and an arbitrary-shaped defect as an example.

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About the authors

L. V. Mikhailov

M.N. Mikheev lnstitute of Metal Physics of Ural Branch of Russian Academy of Sciences

Author for correspondence.
Email: mikhaylov_lv@imp.uran.ru
Russian Federation, 620108, Ekaterinburg, S. Kovalevskoy St., 18

A. V. Mikhailov

M.N. Mikheev lnstitute of Metal Physics of Ural Branch of Russian Academy of Sciences

Email: mikhaylov_lv@imp.uran.ru
Russian Federation, 620108, Ekaterinburg, S. Kovalevskoy St., 18

A. V. Nikitin

M.N. Mikheev lnstitute of Metal Physics of Ural Branch of Russian Academy of Sciences

Email: mikhaylov_lv@imp.uran.ru
Russian Federation, 620108, Ekaterinburg, S. Kovalevskoy St., 18

Ya. G. Smorodinskii

M.N. Mikheev lnstitute of Metal Physics of Ural Branch of Russian Academy of Sciences

Email: mikhaylov_lv@imp.uran.ru
Russian Federation, 620108, Ekaterinburg, S. Kovalevskoy St., 18

V. N. Kostin

M.N. Mikheev lnstitute of Metal Physics of Ural Branch of Russian Academy of Sciences

Email: mikhaylov_lv@imp.uran.ru
Russian Federation, 620108, Ekaterinburg, S. Kovalevskoy St., 18

References

  1. Han W., Que P. An improved genetic local search algorithm for defect reconstruction from MFL signals // Russ. J. Nondestruct. Test. 2005. V. 41. P. 815—821.
  2. Lu S., Liu J., Wu J., Fu X. A Fast Globally Convergent Particle Swarm Optimization for Defect Profile Inversion Using MFL Detector // Machines. 2022. V. 10. P. 1091.
  3. Powell M.J.D. A Direct Search Optimization Method That Models the Objective and Constraint Functions by Linear Interpolation / In: Gomez S., Hennart J.P. (eds.) Advances in Optimization and Numerical Analysis. Mathematics and Its Applications. 1994. V. 275. Springer, Dordrecht.

Supplementary files

Supplementary Files
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1. JATS XML
2. Fig. 1. a — the ratio of the defect geometry (4) and the total H (1), tangential Hτ (2), normal Hn (3); b — the ratio of the defect geometry (1) and the first derivative (2), second derivative (3).

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3. Fig. 2. Results of reconstructing the geometry of defects: a, b — when placing sensors above a defect-free surface for a symmetrical defect and a defect of arbitrary shape, respectively; c, d — when placing sensors above a surface containing a defect, for the same defects.

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