DOI: 10.57760/sciencedb.04226
title: Identification of weak peaks in X-ray fluorescence spectrum analysis based on the hybrid algorithm combining genetic and Levenberg Marquardt algorithm
title: Identification of weak peaks in X-ray fluorescence spectrum analysis based on the hybrid algorithm combining genetic and Levenberg Marquardt algorithm

description: Accurate measurement of cadmium content in rice is of utmost importance to determine if the inspected rice product is safe to people. X-ray fluorescence analysis is frequently used for multi-element analysis because it has characteristics of fast, accurate and nondestructive. However, due to the low content of cadmium in rice, its corresponding characteristics energy peak is relatively weak and is sensitive to the background information in the X-ray energy spectrum. Thus, it is very tough to obtain the accurate values of cadmium content by utilizing traditional X-ray fluorescence analysis. In this paper, the identification of weak peaks of cadmium is much improved by proposing a hybrid algorithm combining genetic algorithm (GA) and Levenberg-Marquardt algorithm (LM). The hybrid algorithm not only takes full advantages of GA and LM respectively but also inhibits their unwanted properties: poor local search ability of GA and locally convergent of LM. The proposed hybrid algorithm is employed to identify weak peaks in X-ray spectra of six contaminated rice samples with different contents of cadmium. Two comparative experiments are conducted to compare the performance between GA, LM and the proposed hybrid algorithm. One of the comparative experiments has the relative error varying with the number of calculations, which aims to verify the accuracy and stability. The results show that the hybrid algorithm is a better option in terms of accuracy and stability. Another comparative experiment of which the average relative error varies with the number of iterations is conducted to verify the computing efficiency. The experiments show that the hybrid algorithm exhibits a faster convergence rate. Two numerical experiments demonstrate that the proposed algorithm can well resolve the identification issue of the cadmium in the X-ray spectra and significantly improve the content measurement accuracy of cadmium in the quality evaluation experiment of rice products.
description: Accurate measurement of cadmium content in rice is of utmost importance to determine if the inspected rice product is safe to people. X-ray fluorescence analysis is frequently used for multi-element analysis because it has characteristics of fast, accurate and nondestructive. However, due to the low content of cadmium in rice, its corresponding characteristics energy peak is relatively weak and is sensitive to the background information in the X-ray energy spectrum. Thus, it is very tough to obtain the accurate values of cadmium content by utilizing traditional X-ray fluorescence analysis. In this paper, the identification of weak peaks of cadmium is much improved by proposing a hybrid algorithm combining genetic algorithm (GA) and Levenberg-Marquardt algorithm (LM). The hybrid algorithm not only takes full advantages of GA and LM respectively but also inhibits their unwanted properties: poor local search ability of GA and locally convergent of LM. The proposed hybrid algorithm is employed to identify weak peaks in X-ray spectra of six contaminated rice samples with different contents of cadmium. Two comparative experiments are conducted to compare the performance between GA, LM and the proposed hybrid algorithm. One of the comparative experiments has the relative error varying with the number of calculations, which aims to verify the accuracy and stability. The results show that the hybrid algorithm is a better option in terms of accuracy and stability. Another comparative experiment of which the average relative error varies with the number of iterations is conducted to verify the computing efficiency. The experiments show that the hybrid algorithm exhibits a faster convergence rate. Two numerical experiments demonstrate that the proposed algorithm can well resolve the identification issue of the cadmium in the X-ray spectra and significantly improve the content measurement accuracy of cadmium in the quality evaluation experiment of rice products.