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- Magnetic flux leakage (2) (entfernen)
Fast defect parameter estimation based on magnetic flux leakage measurements with GMR sensors
(2011)
We present a fast inverse scheme that is capable of simultaneously estimating the parameters depth, opening and length for rectangular 3D geometries of surface-breaking defects. The parameter estimation is realized by an iterative least-squares minimization using the trust-region reflective algorithm. A semi-analytic magnetic dipole model that allows the sensor characteristics to be incorporated is used for predicting the stray magnetic fields. Giant magneto-resistance (GMR) measurements were carried out on a test specimen that includes a series of artificial defects. For the estimation of the defect depths relative errors between 0.6% and 15.9% have been obtained. Due to its very low computational costs, the inverse scheme can suitably be employed in automated production environments.
High-precision magnetic field sensors are of increasing interest in non destructive testing (NDT). In particular GMR-sensors (giant magneto resistance) are qualified because of their high sensitivity, high signal-to-noise ratio and high spatial resolution. We performed magnetic flux leakage measurements of artificial cracks with a GMR-gradiometer and a 3-axes GMR-magnetometer. Cracks of a depth of 44 μm still could be detected with a sufficient high signal-to-noise ratio. A semi-analytic magnetic dipole model was used for swiftly predicting magnetic stray fields. The reliable reconstruction based on measurements of artificial rectangular-shaped defects is demonstrated.