2016•PubMedRequires access

[Optimizing Savitzky-Golay Parameters and Its Smoothing Pretreatment for FTIR Gas Spectra].

An-Xin Zhao, Xiaojun Tang, Zhonghua Zhang, Junhua Liu

Open publisher page 17 citations

Abstract

In the smoothing pretreatment for the quantitative analysis of hydrocarbon mixed gases by Fourier transform infrared analysis (FTIR), the Savitzky- Golay filter is usually used as one of the smoothing preprocessing methods in the Fourier transform infrared spectrum data smoothing pretreatment. However, the parameters of the Savitzky-Golay filter such as the polynomial order and frame size are not easy to decide. There is no one unified choice basis. Users usually adopt multiple sets in the special data set to try, and then select a set of relatively optimal data as the optimizing parameters of the Savitzky-Golay filter. The optimal selection method of the Savitzky-Golay filter parameters was explored, and the concrete calculation equations were deduced according to the relation among the normalized cut-off frequency, the normalized beginning frequency of the stopband, the normalized first side lobe peak frequency of the stopband, the normalized first side lobe peak amplitude with the polynomial order and frame size of the Savitzky-Golay filter parameters. Then when the polynomial order and frame size are set as 8 and 11 respectively according the above conclusion and the characteristics of the actual spectral data, the Savitzky - Golay filter smoothing effect is optimum. Through the acquisition the concentration of 0.1%, 0.2%, 0.5%, 1%, 2%, 5% for the actual CH4 spectra, the relative maximum and minimum error of the raw spectra converted absorbance were 17.230 5% and 0.243 0% respectively, and the relative maximum and minimum error of the smooth spectra converted absorbance were 0.088 0% and 0.088 0% respectively in the second absorption peak. The relative error of converted absorbance was basically stable through the Savitzky-Golay filter after the spectral data preprocessing and it was relatively low, so, it laid a foundation for the late spectral data accurate qualitative and quantitative analysis.

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What this paper is about

In the smoothing pretreatment for the quantitative analysis of hydrocarbon mixed gases by Fourier transform infrared analysis (FTIR), the Savitzky- Golay filter is usually used as one of the smoothing preprocessing methods in the Fourier transform infrared spectrum data smoothing pretreatment. However, the parameters of the Savitzky-Golay filter such as the polynomial order and frame size are not easy to decide. There is no one unified choice basis. Users usually adopt multiple sets in the special data set to try, and then select a set of relatively optimal data as the optimizing parameters of the Savitzky-Golay filter. The optimal selection method of the Savitzky-Golay filter parameters was explored, and the concrete calculation equations were deduced according to the relation among the normalized cut-off frequency, the normalized beginning frequency of the stopband, the normalized first side lobe peak frequency of the stopband, the normalized first side lobe peak amplitude with the polynomial order and frame size of the Savitzky-Golay filter parameters. Then when the polynomial order and frame size are set as 8 and 11 respectively according the above conclusion and the characteristics of the actual spectral data, the Savitzky - Golay filter smoothing effect is optimum. Through the acquisition the concentration of 0.1%, 0.2%, 0.5%, 1%, 2%, 5% for the actual CH4 spectra, the relative maximum and minimum error of the raw spectra converted absorbance were 17.230 5% and 0.243 0% respectively, and the relative maximum and minimum error of the smooth spectra converted absorbance were 0.088 0% and 0.088 0% respectively in the second absorption peak. The relative error of converted absorbance was basically stable through the Savitzky-Golay filter after the spectral data preprocessing and it was relatively low, so, it laid a foundation for the late spectral data accurate qualitative and quantitative analysis.

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Available abstract

In the smoothing pretreatment for the quantitative analysis of hydrocarbon mixed gases by Fourier transform infrared analysis (FTIR), the Savitzky- Golay filter is usually used as one of the smoothing preprocessing methods in the Fourier transform infrared spectrum data smoothing pretreatment. However, the parameters of the Savitzky-Golay filter such as the polynomial order and frame size are not easy to decide. There is no one unified choice basis. Users usually adopt multiple sets in the special data set to try, and then select a set of relatively optimal data as the optimizing parameters of the Savitzky-Golay filter. The optimal selection method of the Savitzky-Golay filter parameters was explored, and the concrete calculation equations were deduced according to the relation among the normalized cut-off frequency, the normalized beginning frequency of the stopband, the normalized first side lobe peak frequency of the stopband, the normalized first side lobe peak amplitude with the polynomial order and frame size of the Savitzky-Golay filter parameters. Then when the polynomial order and frame size are set as 8 and 11 respectively according the above conclusion and the characteristics of the actual spectral data, the Savitzky - Golay filter smoothing effect is optimum. Through the acquisition the concentration of 0.1%, 0.2%, 0.5%, 1%, 2%, 5% for the actual CH4 spectra, the relative maximum and minimum error of the raw spectra converted absorbance were 17.230 5% and 0.243 0% respectively, and the relative maximum and minimum error of the smooth spectra converted absorbance were 0.088 0% and 0.088 0% respectively in the second absorption peak. The relative error of converted absorbance was basically stable through the Savitzky-Golay filter after the spectral data preprocessing and it was relatively low, so, it laid a foundation for the late spectral data accurate qualitative and quantitative analysis.

Key concepts: Binary Golay code, Smoothing, Mathematics, Fourier transform, Filter (signal processing), Polynomial, Absorbance, Algorithm

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