核素识别仪中的自适应变换宽度SNIP算法开发

Development of adaptive width SNIP algorithm in nuclides identification instrument

研究了一种应用于γ散射本底扣除的改进型非线性迭代剥峰算法(Statistics-sensitive Nonlinear Iterative Peak-clipping,SNIP)方法,该方法拟合了峰宽与能量的关系,并通过该关系实时获取峰宽,实现了变换宽度自适应,改善了固定峰宽无法对全谱的散射本底进行准确扣除的缺陷。实验结果表明:本文提出的自适应变换峰宽SNIP算法结构简单,动态效果好,与传统和其他改进的SNIP算法相比,γ能谱的散射本底扣除效果得到了进一步改善,并可以达到优化核素识别的效果,为核素识别方法提供了更多的选择。

[Background] Clipping the scattering background of γ-ray spectrum is one of the important issues in the γ- ray spectrum analysis process. At present, there are many research results in the scattering background clipping methods. Statistically sensitive nonlinear iterative peak-clipping (SNIP) is an ideal choice. However, the original SNIP algorithm uses a fixed width for background clipping, which will cause considerable errors, so researchers have made some improvements to this defect.[Purpose] This study aims to improve the SNIP algorithm to better solve the problem of the original SNIP algorithm, and the improved SNIP algorithms proposed by other researchers.[Methods] First of all, dozens of spectrums measured by different radioactive sources were analyzed and used to obtain the functional relationship between peak width and energy. Then, the function was written into the computer program of SNIP algorithm, so that the width could be calculated instantly. Finally, after the spectrum width was obtained, the remaining SNIP calculation continued to complete the scattering background clipping of the spectrum.[Results] The experimental results show that the adaptive width SNIP algorithm can accurately clip the scattering background of spectrum with advantages of simple structure and good in dynamic effect.[Conclusions] This method can be used to optimize the effect of nuclides identification by accurate calculation of the net peak area providing more choices for nuclides identification instrument.