X射线光谱数据处理平台的优化设计

在低计数率背景下X射线谱的高精度测量受X射线流的统计涨落影响，统计涨落决定了给定探测器能量分辨率的理论极限，而其他因素的影响则可以通过适当的噪声滤除和电子技术来降低。以往关于能量分辨率的研究大多利用谱反卷积对获取到的能谱进行后处理，从而降低特征峰的半高宽（FWHM）。这些后处理方法是基于将获取到的能谱建模为输入能谱和探测器响应函数这两个随机变量的函数，往往计算量极大，执行效率低。针对上述问题，提出一种多脉冲局部平均(MPLA)算法对X射线光谱数据处理平台进行优化，MPLA算法是一种在线实时处理的谱获取方法，该方法在动态窗口内对脉冲幅度值进行了平均。MPLA算法涉及两项可变参数，一是平均窗口的大小r，另一项参数则是每一次平均的脉冲幅度数量n。该算法的执行流程包含以下几个步骤，首先读取第一个脉冲幅度并定位一个平均窗口，读取成功后更新当前平均窗口的脉冲幅度和脉冲个数；第二步，读取下一个脉冲幅度，每次更新后即对平均窗口内的脉冲个数进行判断，当其小于预设的参数n时继续执行第三步，反之则执行第四步；第三步，继续读取下一个脉冲幅度；第四步，对相应平均窗口内的脉冲幅度进行平均，得出的平均数即为需要更新计数的道址，然后再对取平均值的窗口内脉冲幅度和脉冲个数进行清零。本文在理论推导部分研究了应用MPLA过程时原始概率密度函数(PDF)的转换，推导了应用MPLA后得到的概率密度函数的解析表达式，证明了MPLA概率密度转换后具有以下特征：（1）对称分布，MPLA保留了均值和对称性。（2）对于单峰对称分布，MPLA减少方差，锐化分布峰。在实验环节中，以铁矿样品为测量对象，将采用MPLA算法处理后的结果与传统的成谱方法得到的结果进行对比，结果表明在具有正态分布PDF的频谱峰值的典型情况下，即使仅对两个脉冲高度进行平均，变换后峰的FWHM也变窄。

Optimization Design of X-Ray Spectrum Data Processing Platform

Under the background of low counting rate,the high-precision measurement of X-ray spectrum is affected by the statistical fluctuation of X-ray flow,which determines the theoretical limit of given detector energy resolution,while the influence of other factors can be reduced by appropriate noise filtering and electronic technology.Previous studies on energy resolution mostly use spectral deconvolution to post-process the energy spectrum,so as to reduce the full width at half maxima(FWHM)of the characteristic peak.These post-processing methods are based on modeling the obtained energy spectrum as two random variables,i.e.input energy spectrum and detector response function,which is often computationally expensive and inefficient.A multi-pulse local average(MPLA)algorithm is proposed to optimize the X-ray spectrum data processing platform,which is an online real-time spectrum acquisition method.This method averages the pulse amplitude value in the dynamic window.MPLA algorithm involves two variable parameters;one is the average window size r,the other is the average pulse amplitude number n.The implementation process of the algorithm includes the following four steps:step 1,read the first pulse amplitude and locate an average window,update the current average window amplitude and pulse number after reading successfully;step 2,read the next pulse amplitude,judge the number of pulses in the average window after each update,and continue the third step when it is less than the preset parameter n,otherwise.Then perform step 4;step 3,continue to read the next pulse amplitude;step 4,average the pulse amplitude in the corresponding average window,and the average is the channel address to be updated and counted,and then clear the pulse amplitude and pulse number in the average window.In the part of theoretical derivation,this paper studies the transformation of the original probability density function(PDF)in the application of MPLA process,deduces the analytic expression of the probability density function obtained after the application of MPLA and proves the following characteristics after the transformation of MPLA probability density:(1)symmetrical distribution,MPLA retains the mean value and symmetry.(2)For single peak symmetrical distribution,MPLA reduces variance and sharpens distribution peak.In the experiment,the iron ore sample is used as the measurement object,and the results processed by the MPLA algorithm are compared with the results obtained by the traditional spectral method.The results show that in the typical case of the spectrum peak with normal distribution PDF,even if only two pulse heights are averaged,the FWHM of the transformed peak is narrowed.