A Noise Reduction Method of Interferogram Based on Discrete Wavelet Transform for Quantitative Calibration of near Infrared Spectra

2013 ◽  
Vol 834-836 ◽  
pp. 1006-1010 ◽  
Author(s):  
Xue Mei Wu ◽  
Po Yu Lou ◽  
Xiao Hui Yang
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Noise Reduction ◽  
Discrete Wavelet Transform ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Partial Least Square ◽  
Least Square ◽  
Measured Signal ◽  
Discrete Wavelet

Interferogram is the original measured signal of the Fourier transform spectrometer. A new method addressed the problem of noise reduction in inter-ferogram domain is proposed for multivariate calibration of Fourier transform near infrared spectral signals. The method is based on the discrete wavelet transform (DWT). It is used to determination of the ethanol as noise reduction tool for partial least square (PLS) modeling. It is shown that the benefit of the proposed method lies not only in its performance to improve the quality of PLS model and the prediction precision, but also in its simplicity and practicability.

scholarly journals Monitoring of CO2 Absorption Solvent in Natural Gas Process Using Fourier Transform Near-Infrared Spectrometry

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Mohd Yusop Nurida ◽  
Dolmat Norfadilah ◽  
Mohd Rozaiddin Siti Aishah ◽  
Chan Zhe Phak ◽  
Syafiqa M. Saleh
Keyword(s):  
Fourier Transform ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Infrared Spectrometry ◽  
Calibration Model ◽  
Co2 Absorption ◽  
Processing Unit

The analytical methods for the determination of the amine solvent properties do not provide input data for real-time process control and optimization and are labor-intensive, time-consuming, and impractical for studies of dynamic changes in a process. In this study, the potential of nondestructive determination of amine concentration, CO2 loading, and water content in CO2 absorption solvent in the gas processing unit was investigated through Fourier transform near-infrared (FT-NIR) spectroscopy that has the ability to readily carry out multicomponent analysis in association with multivariate analysis methods. The FT-NIR spectra for the solvent were captured and interpreted by using suitable spectra wavenumber regions through multivariate statistical techniques such as partial least square (PLS). The calibration model developed for amine determination had the highest coefficient of determination (R2) of 0.9955 and RMSECV of 0.75%. CO2 calibration model achieved R2 of 0.9902 with RMSECV of 0.25% whereas the water calibration model had R2 of 0.9915 with RMSECV of 1.02%. The statistical evaluation of the validation samples also confirmed that the difference between the actual value and the predicted value from the calibration model was not significantly different and acceptable. Therefore, the amine, CO2, and water models have given a satisfactory result for the concentration determination using the FT-NIR technique. The results of this study indicated that FT-NIR spectroscopy with chemometrics and multivariate technique can be used for the CO2 solvent monitoring to replace the time-consuming and labor-intensive conventional methods.

Discrete Wavelet Transform on Near-Infrared Spectra Analysis for Moisture Determination in Lignitic Coal Samples

2014 ◽  
Vol 513-517 ◽  
pp. 319-322
Author(s):  
Xiao Li Yang ◽  
Neng Bang Hou ◽  
Jun You Shi ◽  
Yan Fang Li
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Near Infrared ◽  
Processing Method ◽  
Discrete Wavelet ◽  
Moisture Determination ◽  
Least Squares Regression ◽  
Spectra Analysis ◽  
Near Infrared Spectra ◽  
Compressed Data

We studied moisture determination in lignitic coal samples through near-infrared (NIR) technique. This research was developed by applying partical least squares regression (PLS) and discrete wavelet transform (DWT). Firstly, the NIR spectra were pre-processed by DWT for fitting and compression. Then, the compressed data were used to build regression model with PLS for moisture determination in coal samples. Three type DWTs were investigated.Determination performance at different resolution scales was studied. The results show that DWT is a very efficient pre-processing method for NIR spectra analysis.

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