分类： 核科学技术 >> 粒子加速器 提交时间： 2023-06-18 合作期刊: 《Nuclear Science and Techniques》
摘要： Direct demodulation method (DDM) was applied to reconstruct -ray spectra. Boosted Richardson-Lucy iteration was introduced into DDM. Monte Carlo method (here GEANT 4) was proposed to calibrate response function and establish response matrix. First, gauss function was regarded as total energy peak. Spectra line was simulated with nine gauss functions. And afterwards DDM was applied to reconstruct the simulated spectra line and determine peak positions and areas. Compared with original spectra, for case that peak position interval was about 1/3 full width half maximum (FWHM), the error of rebuilding peak position was 2 channels. The rest of peaks could be searched accurately. The relative errors of all peaks area were less than 4%. Then, three key factors, including noise, background, response matrix, were discussed. Finally, DDM was applied to calibrate the field NaI gamma spectrometer. The errors of U, Th, K were less than 5%. Comprehensive studies have shown that it is feasible to reconstruct gamma-ray spectra with DDM. DDM can significantly pseudo-improve energy resolution of gamma spectrometer, effectively decompose doublets whose peak potential interval is 1/3 FHWM, and accurately search peak and calculate areas. DDM can restrain noise strongly but is greatly influenced by background. And DDM can improve the accuracy of qualitative and quantitative analysis in combination with the conventional spectrum analysis method.
分类： 核科学技术 >> 粒子加速器 提交时间： 2023-06-18 合作期刊: 《Nuclear Science and Techniques》
摘要： In energy dispersive X-ray fiuorescence (EDXRF), quantitative elemental content analysis becomes difficult due to the existence of the noise, the spectrum peak superposition, element matrix effect, etc. In this paper, a hybrid approach of genetic algorithm (GA) and back propagation (BP) neural network is proposed without considering the complex relationship between the elemental content and peak intensity. The aim of GA-optimized BP is to get better network initial weights and thresholds. The starting point of this approach is that the reciprocal of the mean square error of the initialization BP neural network is set as the fitness value of the individuals in GA; and the initial weights and thresholds are replaced by individuals, then the optimal individual is searched by selecting, crossover and mutation operations, finally a new BP neural network model is established with the optimal initial weights and thresholds. The quantitative analysis results of titanium and iron contents in five types of mineral samples show that the relative errors of 76.7% samples are below 2%, compared to chemical analysis data, which demonstrates the effectiveness of the proposed method.
点击量
通过
点击量
下载量
评论
