Application of AI artificial intelligence dosing technology in heavy medium rapid sedimentation process of coal mining wastewater
| Autor: | XUE Xiaoqiang, LI Jie, HE Gaofeng, WANG Zhihui, WANG Yanbing, XIA Tianfei, YANG Guang, ZHANG Yabin |
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| Jazyk: | čínština |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Gongye shui chuli, Vol 44, Iss 7, Pp 190-196 (2024) |
| Druh dokumentu: | article |
| ISSN: | 1005-829X 2023-1032 |
| DOI: | 10.19965/j.cnki.iwt.2023-1032 |
| Popis: | The heavy medium rapid sedimentation process is widely used in coal mining wastewater, and its process characteristics are multivariate, nonlinear and time-varying. The precision of dosing affects the effluent index and operating costs of the heavy medium rapid sedimentation process. AI artificial intelligence software, as a data science tool, replaces traditional human experience and intuition with digital technology. Compared with traditional dosing control methods, using an AI artificial intelligence dosing system can accurately adjust the dosing amount in real time based on water quantity and quality, ensuring stable effluent quality and enabling early prediction of effluent quality indicators. This project used AI artificial intelligence software to analyze data on existing heavy medium rapid sedimentation processes, identified potential correlations between data, independently created algorithm models, and validated their effectiveness, ultimately achieved the experimental goal of being applicable for guiding production. Under the same industrial control, AI artificial intelligence could save 13.5% of the dosage compared with traditional dosing, achieving energy conservation and consumption reduction. The AI artificial intelligence dosing system can perform deep learning on continuously increasing data, continuously automatically correct model parameters, and make control more accurate. |
| Databáze: | Directory of Open Access Journals |
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