Research on a novel γ-ray spectrum analysis method for low- and intermediate-level radioactive solid waste in nuclear power plants

Accurate nuclide identification in γ-spectrum analysis of low- and intermediate-level radioactive waste with high-purity germanium detectors necessitates initial forced fitting with a nuclide library, yet inaccuracies in library data may lead to misidentification and missing nuclides. To this end, background clipping strategies were hereby analyzed, and a novel deconvolution spectrum analysis method was proposed, which utilized continuous wavelet transform for peak searching and Gaussian first-order derivative quadratic convolution for calculating peak width. Furthermore, to effectively realize the nuclide identification and peak area calculation, a response filter function model was established through the peak shape calibration. By eliminating the need for nuclide library parameter settings prior to overlapping peak separation, the issue of inaccurate matching arising from reliance on the precision of the nuclide library was addressed. Moreover, spectrum analysis experiments were carried out on standard point sources and 200 L drums, and the results were compared and analyzed using GammaVision. Compared to the GammaVision results set by the accurate nuclide library, the area error of strong peaks decreased from 27.5 % to 4.82 %, while that of weak peaks witnessed a decline from 49.98 % to 27.5 %. Finally, the accuracy of the proposed method was verified using the Pakistan Nuclear Library.