Abstract In order to realize the non-invasive and rapid screening of high moisture content contraband by the customs, a detection method combining electrical capacitance tomography (ECT) technology and deep learning is proposed, and the feasibility study is carried out in the simulation environment. Firstly, the ECT sensor suitable for installation on the conveyor is designed, and different package models containing normal objects and contraband with high moisture content are constructed; Then, the capacitance signal data of different package models are obtained by capacitance sensor, and the two-dimensional and three-dimensional image reconstruction are carried out; Finally, in order to make up for the high error rate of manually observed package reconstruction image, a one-dimensional convolutional neural network (1D-CNN) model for adaptive extraction of capacitance signal features is constructed to predict and classify the package model. The experimental results show that the detection accuracy of the proposed method can reach over 98%, and the detection time of a single model is only 10-3 seconds, which can achieve rapid screening of high moisture content prohibited substances.
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2023, Vol. 44 
