Γ-Ray spectral analysis method for real-time detection of fuel element failure. (November 2019)

• Record Type: Journal Article
• Authors: Qin, Guoxiu; Wang, Qimin; Xu, Youning; Chen, Xilin; Li, Fan; Li, Weizhe
• Is Part Of: Annals of nuclear energy. Volume 133(2019)
• Page Start: 221
• Page End: 226
• Publication Date: 2019-11
• Subjects: Spectral analysis -- Gaussian smoothing -- Mathematical morphological transformation -- Gradient descent algorithm, image method; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2019.05.034
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: A kind of γ-spectral analysis method was introduced in this article. Mathematical morphological transformation is used in peak extraction. The gradient descent algorithm is used to search the left and right boundaries. The image method must be adopted to estimate the net area of the peak. We developed a fission-product spectral analysis software. Abstract: Monitoring of fuel element failure in a nuclear reactor is an important process to ensure safe operation of the nuclear reactor. It is feasible to detect fuel element rupture by analysing the radionuclides of fission products and activation products in the primary coolant. To identify the radionuclides in the primary coolant, the most convenient method to measure their activity concentrations is γ-ray spectrometry. A γ-ray spectral analysis method for real-time detection of fuel element failure is proposed in this paper. The method aims to implement a Gaussian smoothing processing for spectral data, extract peaks of spectral data through mathematical morphological transformation, determine left and right peak boundaries with a gradient descent algorithm and finally estimate net peak area with an image method. The method can rapidly recognize a designated key radionuclide from an obtained spectrum and extract peak information to meet the demands of real-time monitoring of fuel element failure in pressurized water reactors.