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- W1677203400 abstract "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 differential impedance profile seen on the specimen's accessible surface, depending on the defect location; the obtained data are used to train a multilayer neural network which provides an analytical approximation of electromagnetic interaction phenomena; a maximum likelihood inversion technique is then proved to be effective in estimating the flaw location." @default.
- W1677203400 created "2016-06-24" @default.
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- W1677203400 date "2002-11-13" @default.
- W1677203400 modified "2023-09-24" @default.
- W1677203400 title "A neural network approach to ECT data inversion for materials quality evaluation" @default.
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- W1677203400 doi "https://doi.org/10.1109/nnsp.2001.943156" @default.
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