2026-10-14T20:05:00Z https://www.scidb.cn/oai

10.57760/sciencedb.hjs.00300 2025-02-21T11:22:49Z

2025-02-21 Implementation and verification of real- time nuclear signal pile-up and separation algorithm based on FPGA doi:10.57760/sciencedb.hjs.00300 en [Background] In the field of nuclear detection, real-time processing of detector signal at high count-rate is necessary. In high count-rate environments, the problem of nuclear signal pile-up can affect the analysis of subsequent results, so it is necessary to process the pile-up signal. The commonly used solution currently is to use pile-up recognition to reject, but this method can cause loss of counts and has limitations in some applications such as timing analysis. [Purpose] This study proposes a real-time pile-up separation algorithm that performs fast/slow shaping processing on the original signal. [Methods] Fast shaping used the triangular shaping method to obtain the arrival time of the nuclear signal to determine whether pile-up occurred; Slow shaping adopted the trapezoidal shaping method to extract the energy information of the nuclear signal. At the same time, by using the symmetrical rising/falling edge features of the trapezoidal signals, the pile-up signal was separated according to the time point of pile-up occurrence to improve the counting performance of the system. The algorithm was simple and computationally efficient, making it easy to implement in field programmable gate array (FPGA). [Results] In the simulation test experiment, the proposed algorithm effectively increased the count rate by 4% to 26.5% while ensuring the accuracy of separation. In the radioactive source experiment, within the tested count rate range, the proposed algorithm effectively increased the count rate by 6.8% to 13.5%. [Conclusion]The results of this study provide a new separation method for pile-up signal processing in high count-rate environments. Nuclear signals pile-up; High count-rate; Trapezoidal shaping; Pile-up separation; FPGA Tang Chao Zhou Wenxiong Tong Teng Zhang Chuanwen Li Daowu Huang Runzhi Pan Liangming Wei Long RESTRICTED dataset Science Data Bank