He jishu (Aug 2024)
An automatic spectral stabilization based on adaptive derivative Gaussian peaking algorithm
Abstract
BackgroundAviation γ spectrometer, measuring at high-altitude with low background counting rate, is prone to spectral line drift caused by factors such as long stable spectral periods and significant temperature effects due to its low background counting rate, hence seriously affects the accuracy of measurement results.PurposeThis study aims to propose an adaptive derivative-Gaussian joint peak search algorithm so as to quickly find and stabilize the peak value of airborne γ-ray spectrometer in low background environment.MethodsFirstly, the process of derivative peak finding algorithm was optimized so that it automatically determined the peak position, channel address, and left and right boundaries based on limited conditions, achieving adaptive transformation background window width deduction of Gaussian peak finding algorithm. Then, a self-developed miniaturized aviation γ spectrometer was used for flight measurement experiments by mounting it on unmanned aerial vehicle, and temperature changing measurement experiments by placing it in a variable temperature oven. Finally, the adaptive derivative gaussian peak finding results were compared and verified with that of traditional derivative peak-seeking algorithm and traditional gaussian peak-seeking algorithm, to ensure the accuracy of the proposed peak finding results and the efficiency of γ spectral stabilization.ResultsThe actual measurement results show that the adaptive derivative Gaussian joint peak finding algorithm has fast calculation speed and high accuracy. With 1 024 aviation tracks γ, the maximum spectral drift of the 40K peak measured by the energy spectrometer within the range of -20 ℃ to 50 ℃, does not exceed ±3 channels.ConclusionsThis study provides a new spectral stabilization method for the accurate measurement of airborne γ-ray spectrum in low background environment.
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