数字化γ能谱测量系统中的脉冲基线估计与扣除方法

Method of pulse baseline estimate and deduction for digital gamma energy spectrometer

在γ能谱测量系统中,基线的估计与扣除一直是脉冲幅度测量处理过程中的一个重要环节。随着γ能谱测量系统的数字化,基线的估计与扣除方法也需要作相应的改进。目前相对复杂的算法只能是先对输入射线脉冲经数字化采样后,再在计算机上编程实现,不适用于以现场可编程门阵列(Field Programmable Gate Array,FPGA)等为核心的数字化系统。部分可以在FPGA上实现的算法,在估计基线时没有充分考虑正常核脉冲信号对基线的影响,精度和实时性相对不足。为解决这一问题,本文提出了一种可在FPGA上实现的脉冲基线估计与扣除方法。该方法通过对采样得到的原始脉冲信号进行去异常滑动平均滤波法,进而求得原始输入脉冲的直流基线,并对该基线进行扣除。而脉冲基线的扣除,必将降低仪器后续处理的复杂度。经实验验证:此方法算法简单、精度好、灵敏度高、可在FPGA上编程实现、可以抑制低频干扰和温度漂移等因素对基线的影响,能够在一定程度上提高能量分辨率,抑制谱线漂移。该方法不仅可以用于数字化γ能谱测量系统,也可以应用于测量其他类型射线(如X射线)的数字化谱仪。

[Background] In the gamma energy spectrum measurement system, estimation and deduction of the baseline has been an important part of pulse amplitude measurement processing. With the digitalization of gamma energy spectrometer, the baseline estimation and deduction method also need to make corresponding improvement. [Purpose] Some relatively complex algorithms which with digital sampling of original pulses only can be realized on a computer, but not suitable for the digital systems which based on field programmable gate array （FPGA）. Some algorithms which could be executed on FPGA didn＇t fully consider the influence of the normal pulse signal, which have poor real-time performance and accuracy. To solve this problem, paper puts forward a kind of new algorithm which could estimate and deduct the pulse baseline. The most important is that it can implement on FPGA. [Methods] This method is called moving average filter after excluding abnormal signal （MAEA）. That is based on the original pulse signal, which obtained by analog-to-digital （A/D） sampling, pulses are viewed as abnormal signals, superimposed on the direct-current （DC） baseline, which need to be deducted. Then DC baseline is obtained by the moving average filtering method. While the pulse DC baseline is deducted by FPGA, the complexity of the instrument for subsequent processing will be lower. [Results] After experimental verification, this method has some characteristics： simple algorithm, well accuracy and high sensitivity. It not only could inhibit the signal＇s influence on the baseline such as low frequency interference and temperature drift, but also could track the change of the baseline real time and accurately and suppress spectral drift to a certain extent. [Conclusion] This method not only can be used for digital gamma energy spectrum measurement system, also can be used applied to other types, such as X-ray digital spectrometer.