Research Article
Design of Infrared Spectrum Information Processing Algorithm for Fourier Infrared Spectrometer
@INPROCEEDINGS{10.1007/978-3-031-18123-8_56, author={Tuo Rui and Ren Wanjie and Hu Guoxing and Cai Chen and Lin Shuai and Zhao Huan}, title={Design of Infrared Spectrum Information Processing Algorithm for Fourier Infrared Spectrometer}, proceedings={Multimedia Technology and Enhanced Learning. 4th EAI International Conference, ICMTEL 2022, Virtual Event, April 15-16, 2022, Proceedings}, proceedings_a={ICMTEL}, year={2022}, month={10}, keywords={Fourier transform infrared spectrometer Spectral information processing Filtering and denoising Baseline correction}, doi={10.1007/978-3-031-18123-8_56} }- Tuo Rui
Ren Wanjie
Hu Guoxing
Cai Chen
Lin Shuai
Zhao Huan
Year: 2022
Design of Infrared Spectrum Information Processing Algorithm for Fourier Infrared Spectrometer
ICMTEL
Springer
DOI: 10.1007/978-3-031-18123-8_56
Abstract
Fourier transform infrared spectrometer has a wide range of applications in many fields. In order to ensure the spectral quality of the spectrometer output, it is necessary to perform certain processing on the original spectrum. After having developed the Fourier transform infrared spectrometer, in this paper we design the infrared spectrum information processing algorithm. The basic transformations of the spectrum, such as spectral derivation, spectral normalization, centralization, and normalization, are realized. The methods of wavelet transform and S-G smoothing filtering are used to filter out the noise. By means of multivariate scattering correction method, the baseline shift and offset phenomenon of the infrared spectrum of the sample are corrected. Combining principal component analysis and Mahalanobis distance, a detection method of abnormal samples is proposed. Through the combination of multiple data processing algorithms, the processed spectra can play a better role in subsequent spectral analysis.
