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| 人工智能在电化学水处理过程中的应用 | |
| 引用本文： | 胡锦文,孟广源,张之杰,张宁,张芯婉,陈鹏,李童,刘勇弟,张乐华. 人工智能在电化学水处理过程中的应用[J]. 化工进展, 2022, 41(Z1): 497-506. DOI: 10.16085/j.issn.1000-6613.2022-0028 |
| 作者姓名： | 胡锦文 孟广源 张之杰 张宁 张芯婉 陈鹏 李童 刘勇弟 张乐华 |
| 作者单位： | 1.华东理工大学高浓度难降解有机废水处理技术国家工程实验室，上海 200237;2.华东理工大学国家环境保护 化工过程环境风险评价与控制重点实验室，上海 200237;3.亳州大学继续教育中心，安徽 亳州 236800 |
| 基金项目： | 国家重点研发计划(2019YFC0408202);国家自然科学基金(21876050) |
| 摘 要： | 近年来，通过人工智能建立的模型可以对工业过程进行精确调控，人工智能应用于电化学水处理技术过程得到了广泛关注。在电化学水处理过程中，人工智能模型可以降低电化学过程的能耗，获取最优能效比。本文对人工智能在电化学水处理的应用进行了综述、分类和归纳，并介绍了其应用方法，概述了人工智能应用于电化学水处理过程的特点、优势以及局限性，比较了用于电化学水处理的人工智能建模与响应面模型、回归模型和经验动力学模型的优劣。进而提出了人工智能在工程应用上的改进思路，为相关研究提供了参考。 |
| 关 键 词： | 电化学 动态建模 人工智能 水处理 环境工程 |
| 收稿时间： | 2022-01-05 |
Application of artificial intelligence model in electrochemical water treatment process |
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| HU Jinwen,MENG Guangyuan,ZHANG Zhijie,ZHANG Ning,ZHANG Xinwan,CHEN Peng,LI Tong,LIU Yongdi,ZHANG Lehua. Application of artificial intelligence model in electrochemical water treatment process[J]. Chemical Industry and Engineering Progress, 2022, 41(Z1): 497-506. DOI: 10.16085/j.issn.1000-6613.2022-0028 | |
| Authors: | HU Jinwen MENG Guangyuan ZHANG Zhijie ZHANG Ning ZHANG Xinwan CHEN Peng LI Tong LIU Yongdi ZHANG Lehua |
| Affiliation: | 1.National Engineering Laboratory for Industrial Wastewater Treatment, East China University of Science and Technology, Shanghai 200237, China 2.State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, East China University of Science and Technology, Shanghai 200237, China 3.Continuing Education Center, Bozhou University, Bozhou 236800, Anhui, China |
| Abstract: | In recent years, the model established by artificial intelligence can accurately regulate and control the industrial process, and the application of artificial intelligence in electrochemical water treatment technology has received extensive attention. In the process of electrochemical water treatment, artificial intelligence model can reduce the energy consumption of electrochemical process and obtain the optimal energy efficiency ratio. In this paper, the application of artificial intelligence in electrochemical water treatment is summarized, classified and summarized, and its application methods are introduced. The characteristics, advantages and limitations of artificial intelligence in electrochemical water treatment process are summarized, and the advantages and disadvantages of artificial intelligence modeling, response surface model, regression model and empirical dynamic model used in electrochemical water treatment are compared. Furthermore, this paper puts forward the improvement ideas of artificial intelligence in engineering application, which provides a reference for related research. |
| Keywords: | electrochemistry dynamic modeling artificial intelligence waste water treatment environmental engineering |
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