A Neural Network Approach to Ect Data Inversion for Materials Quality Evaluation
نویسندگان
چکیده
The aim of this paper is to present a novel NDT technique for detecting and estimating the location of a defect inside a conductive object by neural network based processing of eddy-current data. The electromagnetic interaction between the conductive specimen and the eddy-current probe is simulated by a 3D numerical technique, which reproduces the diierential impedance proole seen on the specimen's accessible surface, depending on the defect location; the obtained data are used to train a mul-tilayer neural network which provides an analytical approximation of electromagnetic interaction phenomena; a maximum likelihood inversion technique is then proved to be eeective in estimating the aw location.
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