Construction and application of the prediction model of outlet moisture in the loosening and conditioning process

Zijuan Li; Zixian Feng; Liyuan Zhao; Jiaojiao Chen; Yang Gao; Shuo Sun; Yanling Ma

doi:10.1117/12.2635392

6 May 2022 Construction and application of the prediction model of outlet moisture in the loosening and conditioning process

Zijuan Li, Zixian Feng, Liyuan Zhao, Jiaojiao Chen, Yang Gao, Shuo Sun, Yanling Ma

Author Affiliations +

Proceedings Volume 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022); 122562Y (2022) https://doi.org/10.1117/12.2635392
Event: 2022 International Conference on Electronic Information Engineering, Big Data and Computer Technology, 2022, Sanya, China

Abstract

In order to ensure the stability of the quality of the tobacco in the loosening and conditioning process and the accuracy of the measuring instruments, verification can be carried out by constructing a mass transfer prediction model and an online verification process. Statistically analyze the input and output of materials in the production process of loosening and conditioning process, and obtain the prediction model of dry matter quality, water matter quality, moisture steam conversion coefficient in tobacco leaves and outlet moisture gas. After production experiment verification, the relative error range between the predicted value of the outlet moisture of the tobacco leaves and the actual measured value is maintained at ±0.48%, and the average relative error is 0.21%, which is less than 0.5%, which meets the requirements of process standards, and the model is accurate and reliable. Based on the material balance forecasting model, the theoretical value is compared with the actual value to realize the online comparison and verification of the moisture meter, which has a certain guiding role in improving the accuracy and verification efficiency of the measuring instrument.

Citation Download Citation

Zijuan Li, Zixian Feng, Liyuan Zhao, Jiaojiao Chen, Yang Gao, Shuo Sun, and Yanling Ma "Construction and application of the prediction model of outlet moisture in the loosening and conditioning process", Proc. SPIE 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022), 122562Y (6 May 2022); https://doi.org/10.1117/12.2635392

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