Research on determining the end point of carbon kneading based on LSTM algorithm

Hongbo Lv; Miantong Sun; Jun Tie; Rentao Zhao; Ruoqing Zhang

doi:10.1117/12.3005985

10 October 2023 Research on determining the end point of carbon kneading based on LSTM algorithm

Hongbo Lv, Miantong Sun, Jun Tie, Rentao Zhao, Ruoqing Zhang

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127990B (2023) https://doi.org/10.1117/12.3005985
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

As an important raw material in the process of aluminum electrolysis, the quality of prebaked anode is directly related to the technical indexes such as carbon consumption, production stability and aluminum purity of aluminum electrolysis. As an important process in the production of prebaked anodes, the end point of kneading affects the automation of raw anode production process, production efficiency and product qualification rate. In this paper, the collected data of the kneading process are processed and the model is established by using LSTM algorithm in machine learning, which can accurately predict the remaining time of kneading and realize the judgment of the end point of carbon kneading, and provide guidance value to the actual production.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hongbo Lv, Miantong Sun, Jun Tie, Rentao Zhao, and Ruoqing Zhang "Research on determining the end point of carbon kneading based on LSTM algorithm", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127990B (10 October 2023); https://doi.org/10.1117/12.3005985

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