Online Determination on the Properties of Naphtha as the Ethylene Feedstock Using Near-Infrared Spectroscopy
- Authors: Chen F.1, Tianbo L.2, Guihua H.1, Minglei Y.1, Jian L.1,3
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Affiliations:
- Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology
- Sinopec Jinan company
- Qingyuan Innovation Laboratory
- Issue: Vol 63, No 5 (2023)
- Pages: 688-700
- Section: Articles
- URL: https://journals.rcsi.science/0028-2421/article/view/249598
- DOI: https://doi.org/10.31857/S0028242123050076
- EDN: https://elibrary.ru/RZPYBP
- ID: 249598
Cite item
Abstract
Providing real-time information on the properties of naphtha as the ethylene feedstock within the minimal time is significant for improvement of the process simulation, control, and real-time optimization. To develop models predicting naphtha properties for different pre-processing methods, an online full transmittance near-infrared (NIR) spectrum measurement system has been used along with the principal component regression and partial least squares (PLS) methods. The results show that the Savitzky-Golay smoothing combined with the first-derivative pre-processing provides the best denoising effect compared to other methods. The predicted relative errors of the NIR models developed by PLS, especially for the cutting temperature points of the test set, basically make 1‒5% indicating it can be used to create good NIR prediction models for the on-line determination of naphtha properties.
About the authors
Fan Chen
Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology
Email: petrochem@ips.ac.ru
200237, Shanghai, China
Liu Tianbo
Sinopec Jinan company
Email: petrochem@ips.ac.ru
250102, Jinan, China
Hu Guihua
Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology
Email: petrochem@ips.ac.ru
200237, Shanghai, China
Yang Minglei
Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology
Email: petrochem@ips.ac.ru
200237, Shanghai, China
Long Jian
Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology; Qingyuan Innovation Laboratory
Author for correspondence.
Email: longjian@ecust.edu.cn
200237, Shanghai, China; 362801, Quanzhou, China
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