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.
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