CLYC探测器n/γ聚类甄别方法研究

Study on n/γ Discrimination Method Based on Clustering Analysis for CLYC Detector

  • 摘要: 为了高性能分辨探测中子与γ射线,搭建了一套基于Cs2LiYCl6:Ce3+(CLYC)探测器和数字示波器的数字化核脉冲采集系统。通过Matlab编程,研究了系统聚类法和K-means聚类法两种n/γ脉冲波形甄别方法,并与传统的电荷比较法进行了对比。结果表明,两种聚类法均可准确分辨脉冲类别,K-means聚类法在计算时间和内存占用方面更具优势,有利于实时脉冲处理。该研究为研制基于CLYC探测器的n/γ双模式探测谱仪提供了一种有用的脉冲波形甄别技术解决方案。

     

    Abstract: In order to discriminate neutron and γ ray with high performance, a digital nuclear pulse sampling system based on a Cs2LiYCl6: Ce3+ (CLYC) detector and a digital oscilloscope was set up. By Matlab programming, two pulse shape discrimination methods, including hierarchical clustering method and K-means clustering method were studied, and were compared with the traditional charge comparison method. The results show that both of these two methods can discriminate neutron and γ pulses accurately. The K-means clustering method is better for less computing time and memory consumption, and makes profit for real-time pulse discriminating. This research provides a useful pulse shape discrimination solution to develop the n/γ dual-mode spectrometer with CLYC detector.

     

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