Visual evaluation of cracks in the steel under the coating is an important topic in the nondestructive testing field. In this paper, the double gradient fusion algorithm is presented for the visualization of irregular cracks using the composite alternating current field measurement and magnetic flux leakage (ACFM-MFL) testing method. A finite element method model of the ACFM-MFL is developed to extract the disturbed current and distorted magnetic field caused by the irregular crack. The double gradient fusion algorithm is presented to reconstruct the surface morphology of the irregular crack. The ACFM-MFL testing system is developed to detect and evaluate the irregular crack in the steel under the coating using the double gradient fusion algorithm. The results show that the surface morphology of the irregular crack can be reconstructed accurately and evaluated visually in the steel under the coating by the double gradient fusion algorithm using the composite ACFM-MFL testing method.

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Visual Evaluation of Irregular Cracks in Steel by Double Gradient Fusion Algorithm Using Composite ACFM-MFL Testing Method

  • Wei Li,
  • Xin’an Yuan,
  • Jianming Zhao,
  • Xiaokang Yin,
  • Xiao Li

摘要

Visual evaluation of cracks in the steel under the coating is an important topic in the nondestructive testing field. In this paper, the double gradient fusion algorithm is presented for the visualization of irregular cracks using the composite alternating current field measurement and magnetic flux leakage (ACFM-MFL) testing method. A finite element method model of the ACFM-MFL is developed to extract the disturbed current and distorted magnetic field caused by the irregular crack. The double gradient fusion algorithm is presented to reconstruct the surface morphology of the irregular crack. The ACFM-MFL testing system is developed to detect and evaluate the irregular crack in the steel under the coating using the double gradient fusion algorithm. The results show that the surface morphology of the irregular crack can be reconstructed accurately and evaluated visually in the steel under the coating by the double gradient fusion algorithm using the composite ACFM-MFL testing method.