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Research on ICP-AES Spectral Baseline Correction Method Based on DE Algorithm and NURBS Curve |
LIAN Xiao-qin1, 2, CHEN Yan-ming1, 2, WANG Yu-qiao1, 2, LIU Yu1, 2 |
1. School of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China
2. China Light Industry Key Laboratory of Industrial Internet and Big Data, Beijing Technology and Business University, Beijing
100048, China
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Abstract Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) analysis method is a commonly used solution element concentration analysis method. However, in the process of ICP-AES measurement, due to temperature drift, stray light and instrument dark current, etc., the spectrum often has a certain degree of the baseline drift phenomenon, resulting in errors in the measurement results of element spectral intensity values, which in turn affects the quantification of element concentrations. Therefore, baseline correction is one of the necessary links in the ICP-AES analysis method. In this paper, the traditional spectral baseline correction method is briefly analyzed, and on this basis, a ICP-AES spectral baseline drift correction method based on non-uniform B-spline curve and differential evolution algorithm is designed; Firstly, it is verified that the probability density distribution of noise in the spectral signal obeys the Gaussian distribution, then the original spectrum is preprocessed, and the spectral signal is denoised by Gaussian filtering; Then, the standard deviation of the minimum value sequence in the process of spectral baseline correction is used as the evaluation index, the non-uniform B-spline curve is used as the baseline model, and the control point sequence C and the internal point sequence T of the curve are used as the characteristic parameters of the evaluation function to establish the ICP- AES spectral baseline correction evaluation function, so that the spectral baseline correction problem can be converted into the problem of solving the global optimal solution of the characteristic parameters of the evaluation function; Finally, this paper briefly introduces the process of the differential evolution algorithm, and uses the differential evolution algorithm to solve the global optimal solution of the characteristic parameters when the evaluation function achieves the minimum value, that is, the control point sequence C and the interior point sequence T of the non-uniform B-spline curve, and fit the corresponding non-uniform B-spline curve as the spectral baseline to realize the baseline correction of the ICP-AES spectrum. A dataset of measured ICP-AES spectral data is used to verify the baseline drift correction method proposed in this paper. The experimental results show that the ICP-AES spectral baseline correction method was based on the differential evolution algorithm. And the non-uniform B-spline curve proposed in this paper can accurately calculate the control point sequence C and the internal point sequence T of the non-uniform B-spline curve and fit the suitable spectral baseline, which enables baseline correction of ICP-AES spectra. The method can overcome the limitation of the non-uniform B-spline curve in the field of spectral baseline correction and provide a technical basis for the subsequent quantitative analysis of element content.
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Received: 2021-10-20
Accepted: 2022-04-12
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