Study on Correction Algorithms of Characteristic Peak Drift in X-Ray Spectrum
TANG Lin1,2,3, LIAO Xian-li1*, LIU Xing-yue1, ZHAO Yong-xin1, LI Yue-peng1, YU Song-ke1,3
1. School of Information Science and Engineering, Chengdu University, Chengdu 610106, China
2. Key Laboratory of Pattern Recognition and Intelligent Information Processing, Institutions of Higher Education of Sichuan Provinice, Chengdu University, Chengdu 610106, China
3. Geomathematics Key Laboratory of Sichuan Province，Chengdu University of Techonolgy, Chengdu 610059, China
Abstract：In order to solve the problem of abrupt pulse appearing in switch reset preamplifier of high-performance silicon drift detector using digital slow triangulation algorithm and the problem of characteristic peak drift caused by amplitude damage of such pulse after forming, a correction algorithm of characteristic peak drift based on abrupt pulse repair is proposed. The algorithm includes the following processes. Firstly, the weak current signal output by the former circuit is converted into the negative exponential signal by CR differential circuit，and then, the amplitude range of the negative index signal amplified by the three-stage amplifier is 0～2 V, and the amplitude range is kept in the processing range of the back-end analog-to-digital converter. The digital negative index pulse sequence is obtained by the analog-to-digital conversion of the amplified negative index signal. Through the judgment of the sampling points of the above negative index pulse sequence, when the continuous multiple sampling points are zero, the pulse is marked as abrupt pulses. At last, the fast and slow correction algorithms are used to repair the abrupt pulses, and the repaired negative index pulse sequence is processed by digital trapezoid forming, and the forming results are stored in FIFO for multi-channel spectrum generation. In the experiment, self-made iron ore samples were taken as the measurement object, and the uncorrected original spectrum is compared with the spectrum obtained by different correction methods. The results show that the counting rate of the shadow peaks of the corrected Fe and Sr characteristic peaks in the channel address range is significantly lower than that of the uncorrected original spectrum. At the same time, the number of the channel address intervals of the two characteristic peaks of Fe and Sr is significantly higher than that of uncorrected. Because the drift of the counting rate of the characteristic peak is the root cause of the shadow peak, the decreasing value of the counting rate of the same element in the shadow peak area should be consistent with the increasing value of the counting rate in the characteristic peak area. The results show that the difference of counting rate between the fast correction and slow correction of the shadow peak and the characteristic peak of Fe element is basically consistent with this trend, but the difference of counting rate between the fast correction and the fast correction of strontium element shadow peak and the characteristic peak of Sr element is large, which does not conform to the rule that the decrease of the shadow peak count is the increase of the characteristic peak count. The basic reason for this result is that the fast correction is not complete for the repair of abrupt pulse, and the slow correction can better achieve the repair of all sampling points. The final repair efficiency also shows that for the same interval, the slow correction method has higher repair efficiency and better correction effect for the characteristic peak drift. The results show that the correction algorithm can effectively eliminate the shadow peak in front of the characteristic peak and realize the correction of the characteristic peak drift, which is of great significance for obtaining the fine X-ray spectrum.
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