Citation: LING Meng-Xuan, LU Su-Min, SUN Hao, LIU Dan, BIAN Xi-Hui. X-ray Diffraction Spectral Denoising Based on Empirical Mode Decomposition and t-Test[J]. Chinese Journal of Analytical Chemistry, ;2023, 51(3): 445-453. doi: 10.19756/j.issn.0253-3820.221534 shu

X-ray Diffraction Spectral Denoising Based on Empirical Mode Decomposition and t-Test

LING Meng-Xuan ¹ ,
LU Su-Min ¹ ,
SUN Hao ¹ ,
LIU Dan ¹ ,
BIAN Xi-Hui ^1,2,,

1.
School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, China;
2.
National Medical Products Administration Key Laboratory for Technology Research and Evaluation of Drug Products, Shandong University, Jinan 250012, China

Corresponding author: BIAN Xi-Hui, bianxihui@163.com
Received Date: 30 October 2022
Revised Date: 3 February 2023

Fund Project: Supported by the Open Projects Fund of National Medical Products Administration Key Laboratory for Technology Research and Evaluation of Drug Products (No. 2022TREDP04) and the Tianjin Science and Technology Program (No. 21ZYJDJC00100).

X-ray diffraction (XRD) has been widely used in the field of analytical chemistry because it can quickly analyze the composition of materials and the structure and morphology of atoms or molecules inside materials. However, due to the influence of instrument vibration, electromagnetic interference and other factors, the XRD spectrum measured by X-ray diffractometer is extremely noisy. Therefore, in this study, empirical mode decomposition (EMD) combined with t-test was introduced for XRD spectral denoising. Firstly, the XRD spectrum was decomposed by EMD to obtain a series of intrinsic mode function (IMF) components. The high frequency components represented noise and the low frequency components represented useful information. However, sometimes the noise was indistinguishable from useful information. Therefore, the statistical t-test method was introduced in this study to determine the significant difference between the mean of IMFs and zero. Finally, the components with no significant difference were deleted, and the components with significant difference were reconstructed to obtain denosied XRD spectrum. The feasibility of this method was verified by a simulated XRD spectrum and two measured XRD spectrum. The results showed that EMD combined with t-test could effectively remove the noise in XRD spectrum in comparison with Savitzky-Golay (SG) smoothing.
- Denoising,
- Empirical mode decomposition,
- t-Test,
- X-ray diffraction,
- Simulation signal
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