Abstract

Magnetic flux leakage technique is used for defect detection inside a magnetically permeable bar by measuring the leakage fields outside the bar. Defects of varying sizes in a magnetically permeable bar have been modelled as localized anti-dipoles with different moments. These defect locations and moments have to be determined based on the measurement of the leakage fields in the presence of random noise. Multiple Signal Classification (MUSIC) approach has been used to identify the defect locations and the moments of these defects. After finding the location of the first dipole representing the larger defect, using orthogonal projection of the measured magnetic field data away from the first defect location, location of the next dipole is identified by MUSIC. This process is continued until all the defects are exhausted. The leakage fields from three deeply buried defects were simulated by direct forward calculation and the resulting data were utilized for inversion using this approach. It has been possible to identify the number of defects and their locations by this approach even in the presence of reasonable levels of additive noise.

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