The Study For Spectral Analysis Methods Of Hpge Gamma Spectrometer

HPGe gamma spectrometer and NaI(Tl) gamma spectrometer are the mostcommonly used spectrometer in radioactive measurement, but amost all radioactivesoil samples are measured by HPGe gamma spectrometer in environmental protectionsystem. HPGe gamma spectrometer has better performance in energy resolution andlinearity. However, there are still some overlapping peaks difficult to distinguish, andalso statistical fluctuations and scatter background have the effect on the quantitativeanalysis of nuclides in the practical measurement.This article is based on the investigation on the radioactivity levels of associatedore in Guizhou province. With the comprehensive comparison of the currentsituation concerning data processing and analysis, this article mainly discusses theresearch about HPGe gamma spectrum analysis in Peak Search、 backgrounddeduction and use Gaussian deconvolution response matrix to parse γ spectrum.（1）The Research on Peak Search: The research uses the simple comparisonmethod and the method of first derivative. In the simple comparison method, we usegravity method and fitting method for the calculation of peak position and gravitymethod is better; The results will be more accurate if the spectrum has beensmoothed before searching the peak.In the method of first derivative, theperformance is poor for the spectrum has been smoothed. The result is just theopposite for the spectrum has not been smoothed.（2）The Research on background deduction: The research uses SNIPbackground subtraction and robust regression background subtraction. Afterpreliminary tests, SNIP method is more simple and practical. The result of robustregression for HPGe spectrometer which has a wide range of spectral did not achievethe desired effect, We need line segmentation processing.（3）The study of using Gaussian deconvolution response matrix to parse γspectrum: The paper is mainly aimed at HPGe γ spectrum of spectral data, we buildgaussian response matrix based on the different FWHM and analysis Gamma energyspectrum data by deconvolution. As can be seen from the results, spectrum deconvolution can improve resolution and separate the overlapping peaks, and also itcan be applied for further quantitative analysis.