| Issue |
E3S Web Conf.
Volume 522, 2024
2023 9th International Symposium on Vehicle Emission Supervision and Environment Protection (VESEP2023)
|
|
|---|---|---|
| Article Number | 01028 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/e3sconf/202452201028 | |
| Published online | 07 May 2024 | |
Research on optimization algorithm of molecular distillation process parameters based on ELM-ADHDP
1 School of Mechatronic Engineering, Changchun University of Technology, China
2 School of Electrical and Electronic Engineering, Changchun University of Technology, China
3 Information Construction Office, Changchun University of Technology, China
* Corresponding author: lihui@ccut.edu.cn
In the traditional molecular distillation process, there are also large differences in the process parameters of different extracts in the process of separation and purification, and there are equipment aging and site condition changes in the project of equipment operation, and the setting of process parameters is only based on the experience of the operator, which greatly reduces the effect of separation and purification. In this paper, ELM-ADHDP is used to optimize the process parameters of the molecular distillation system, determine the best process parameters, achieve accurate and optimized control of the equipment, improve the efficiency of separation and purification, and reduce the energy consumption and the dependence on manual experience.
Key words: Molecular distillation / ADHDP / Optimization algorithm / Extreme learning machine
© The Authors, published by EDP Sciences, 2024
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