Nuclear spectrum data smoothing method based on multi-parameter model

Abstract

The invention discloses a nuclear spectrum data smoothing method based on a multi-parameter model. The method comprises the steps of obtaining nuclear spectrum data; smoothing the nuclear energy spectrum data through a multi-parameter recursion function model based on a Sallen-Key filter circuit, and analyzing peak position, peak shape and peak area information of the smoothed nuclear energy spectrum under different parameters to obtain the nuclear energy spectrum data under the optimal smoothing parameters.. According to the invention, the peak position, the peak shape, and the peak area of the smoothed waveform are adjusted by changing the values of related parameters; the defects that the smoothing effect of an arithmetic moving average method and a gravity center method is not ideal, and a polynomial least square fitting method, a Fourier transformation method and a discrete function convolution transformation method are complex in algorithm and poor in real-time performance are overcome, and a new implementation mode is provided for rapid and effective smoothing of nuclear spectrum data.

Description

technical field [0001] The invention relates to the technical field of nuclear energy spectrum data processing, and more specifically relates to a method for smoothing nuclear energy spectrum data based on a multi-parameter model. Background technique [0002] As one of the most important means in nuclear analysis methods, nuclear energy spectrum analysis can directly or indirectly obtain important information such as the structure of substances, the types and contents of constituent elements, etc. through the acquisition and analysis of the energy spectrum of the researched object. And it is widely used in industry, agriculture, medicine, aerospace, environment, energy, national security and other fields due to its advantages of high sensitivity, good accuracy and low destructiveness. [0003] Due to the statistical nature of nuclear decay and measurement, when the count in the nuclear spectrum data is small, the statistical fluctuation of the count is relatively large, and...

AI Technical Summary

Problems solved by technology

Among them, the algorithm of arithmetic moving average method and center of gravity method is simple, but the smoothing effect is not ideal, and it is generally used in the smoothing of nuclear energy spectrum data with obvious spectral peaks; polynomial least squares fitting method, Fourier transform method, discrete function convolution transformation method algorithm Complex and poor real-time performance

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