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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.
GMR sensors are widely used in many industrial segments such as information technology, automotive, automation and production, and safety applications. Each area requires an adaption of the sensor arrangement in terms of size adaption and alignment with respect to the field source involved. This paper deals with an analysis of geometric sensor parameters and the arrangement of GMR sensors providing a design roadmap for non-destructive testing (NDT) applications. For this purpose we use an analytical model simulating the magnetic flux leakage (MFL) distribution of surface breaking defects and investigate the flux leakage signal as a function of various sensor parameters. Our calculations show both the influence of sensor length and height and that when detecting the magnetic flux leakage of µm sized defects a gradiometer base line of 250 µm leads to a signal strength loss of less than 10% in comparison with a magnetometer response. To validate the simulation results we finally performed measurements with a GMR magnetometer sensor on a test plate with artificial µm-range cracks. The differences between simulation and measurement are below 6%. We report on the routes for a GMR gradiometer design as a basis for the fabrication of NDT-adapted sensor arrays. The results are also helpful for the use of GMR in other application when it comes to measure positions, lengths, angles or electrical currents.
Size adapted GMR arrays for the automated inspection of surface breaking cracks in roller bearings
(2014)
Their small size together with a remarkable field sensitivity are the most prominent features of present-day GMR sensors paving the way for various applications in automated non-destructive testing (NDT). This work presents a prototype for fast and automated magnetic testing of roller bearings. A local magnetization unit excites the magnetic field inside the bearing. As a result of a design study and the following wafer fabrication the probe was equipped with NDT-adapted GMR sensor arrays in which 48 elements measures the field response. The detection of artificial and 40 µm deep defects could be resolved with a SNR better than 20 dB. In addition, we report of first results of a POD (Probability of Detection) analysis using GMR sensors to investigate bearings with EDM (electronic discharge machining) notches having depths down to 10 µm. Finally, we estimate successfully the depth of a 57 µm notch from the measured data.
Micro-cracks in a magnetized ferromagnetic material cause stray fields that can be observed using giant magnetoresistive (GMR) sensors. This work investigates the applicability of GMR sensors to the non-destructive evaluation of micro-cracks via the observation of stray fields. For this purpose, our measurement setup is assessed using a fast new sensitivity analysis based on adjoint states, employing the finite-element method. A model for the GMR sensor is developed and verified. We are able to resolve micro-cracks with an opening of 3 µm and a depth of 30 µm. GMR positioning inaccuracies are analyzed.