Recognition of Fission Signals Based on Wavelet Analysis and Neural Network

Abstract: Because of the particularity of the uranium components, the nondestructive measuring technique is needed to detect the radioactivity of the component in certain container and identify their property to recognize all kinds of uranium components. This paper establishes a set of samples with the same shape, different weight and abundance of uranium by simulation. Secondly the cross-correlation function of timerelation signal between the source detector and the detector could be calculated. Lastly the result of crosscorrelation functions is through micro-wavelet analysis to obtain feature vector which is related to the quality and abundance property of target uranium components. This vector is used to train neural network and help to identify the quality and abundance of unknown uranium components.
Keywords: micro-wavelet analysis, neural network, uranium component
Author: Li Li, Liu Keqi, Hu Gen
Journal Code: jptkomputergg160299

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