摘要:
γ谱分析是一种重要的放射性核素定量分析方法.弱峰的检测和重叠峰的分解是γ谱分析中的难点.为了解决这两个问题,基于压缩感知理论,提出了一种新的γ谱分析方法.这一方法从谱仪对γ谱调制的物理机理出发,通过数学建模,将γ谱分析转化为一个以真实γ谱为解的求逆问题,并在压缩感知理论框架下,运用γ谱特征峰的稀疏性,进行逆问题的求解,直接获得γ谱的估计结果.数值模拟结果和蒙特卡洛模拟结果表明:该方法能在降低统计涨落的同时,有效减小谱仪调制带来的能谱展宽,从而提高γ谱分析精度.
关键词:
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γ谱分析
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压缩感知
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非线性
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逆问题
Abstract:
The gamma-ray spectrum analysis is an important method for quantitative analysis of radionuclide. Although widely used, the weak peak identification and overlapping peaks resolution are still difficult for gamma-ray spectrum analysis. To solve the problem, a new method based on compressed sensing is proposed for improving gamma-ray spectrum analysis in this paper. The proposed method models physical modulation of gamma spectrometer as a linear equation, and formulates the gamma-ray spectrum analysis as a corresponding inverse problem. The true gamma spectrum is obtained by solving the inverse problem by applying sparsity constraint under the framework of compressed sensing. The feasibility of the proposed method is demonstrated by both numerical simulation and Monte Carlo simulation experiments. Results demonstrate that the proposed method can simultaneously resolve overlapped peaks and reduce the fluctuations of gamma-ray spectrum, effectively improving the accuracy of gamma-ray spectrum analysis.
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