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Towards end-to-end pulsed eddy current classification and regression with CNN
[article]
2019
arXiv
pre-print
Pulsed eddy current (PEC) is an effective electromagnetic non-destructive inspection (NDI) technique for metal materials, which has already been widely adopted in detecting cracking and corrosion in some multi-layer structures. Automatically inspecting the defects in these structures would be conducive to further analysis and treatment of them. In this paper, we propose an effective end-to-end model using convolutional neural networks (CNN) to learn effective features from PEC data.
arXiv:1902.08553v1
fatcat:tq6lql5rrvb3fmx2znm7tirop4