Citation: WEN Xiao-Yan, XU Yan-Yan, LI Mao-Gang, ZHANG Tian-Long, TANG Hong-Sheng, LI Hua. Study on Transfer Performance of Methanol Gasoline Quantitative Analysis Model Based on Near-Infrared Spectroscopy Combined with Piecewise Direct Standardization[J]. Chinese Journal of Analytical Chemistry, ;2021, 49(10): 1758-1765. doi: 10.19756/j.issn.0253-3820.211033 shu

Study on Transfer Performance of Methanol Gasoline Quantitative Analysis Model Based on Near-Infrared Spectroscopy Combined with Piecewise Direct Standardization

1.
Xi'an Modern Chemistry Research Institute, Xi'an 710065, China;
2.
Key Laboratory of Synthetic and Natural Functional Molecule of the Ministry of Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710127, China;
3.
College of Chemistry and Chemical Engineering, Xi'an Shiyou University, Xi'an 710065, China

Corresponding author: TANG Hong-Sheng, LI Hua,
Received Date: 14 January 2021
Revised Date: 8 June 2021

Fund Project: Supported by the National Natural Science Foundation of China (Nos.22073074, 21873076, 21675123, 21605123).

The transfer performance of near infrared (NIR) spectrometry quantitative analysis model for methanol gasoline was studied based on piecewise direct standardization (PDS) algorithm. First, in the experimental environment, 20 methanol gasoline samples were prepared and their NIR spectra were collected. Secondly, the influence of different NIR wave ranges as input variables on the prediction performance of the model was explored. Thirdly, the effects of different spectral pretreatment methods on the NIR spectra were investigated. Based on the spectral data preprocessed by normalization (Nor) and multiple scattering correction (MSC), the initial PLS calibration model and PDS-PLS transfer model were constructed. Finally, to further verify the prediction performance of PDS-PLS model, PLS model based on original spectrum, domain adaptive (DA) and kernel domain adaptive (KDA) were constructed. The results showed that, compared with other PLS models, the model constructed by PDS-PLS calibration model had a significant improvement on the prediction performance. The coefficient of determination of prediction set (R_P²) was 0.9984, the root mean square error of prediction set (RMSE_P) was 0.0056, and the mean relative error (MRE_P) was 4.36%. The results showed that PDS-PLS was a simple and efficient model transfer method for NIR quantitative analysis of methanol gasoline.
- Methanol gasoline,
- Calibration transfer,
- Near infrared spectroscopy,
- Partial least squares
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沈阳化工大学材料科学与工程学院沈阳 110142