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城市污水处理过程异常工况识别和抑制研究

韩红桂 伍小龙 张璐 乔俊飞

韩红桂, 伍小龙, 张璐, 乔俊飞. 城市污水处理过程异常工况识别和抑制研究. 自动化学报, 2018, 44(11): 1971-1984. doi: 10.16383/j.aas.2018.c180439
引用本文: 韩红桂, 伍小龙, 张璐, 乔俊飞. 城市污水处理过程异常工况识别和抑制研究. 自动化学报, 2018, 44(11): 1971-1984. doi: 10.16383/j.aas.2018.c180439
HAN Hong-Gui, WU Xiao-Long, ZHANG Lu, QIAO Jun-Fei. Identification and Suppression of Abnormal Conditions in Municipal Wastewater Treatment Process. ACTA AUTOMATICA SINICA, 2018, 44(11): 1971-1984. doi: 10.16383/j.aas.2018.c180439
Citation: HAN Hong-Gui, WU Xiao-Long, ZHANG Lu, QIAO Jun-Fei. Identification and Suppression of Abnormal Conditions in Municipal Wastewater Treatment Process. ACTA AUTOMATICA SINICA, 2018, 44(11): 1971-1984. doi: 10.16383/j.aas.2018.c180439

城市污水处理过程异常工况识别和抑制研究

doi: 10.16383/j.aas.2018.c180439
基金项目: 

国家自然科学基金 61533002

教育部-中国移动科研基金项目 MCM2017030

国家自然科学基金 61622301

北京市自然科学基金项目 4172005

详细信息
    作者简介:

    伍小龙  北京工业大学信息学部博士研究生.2012年获得北京工业大学控制科学与工程硕士学位.主要研究方向为城市污水处理过程智能自组织控制.E-mail:lewis_wxl@sina.com

    张璐  北京工业大学信息学部博士研究生.2014年获得菏泽学院控制科学与工程学士学位.主要研究方向为城市污水处理过程多目标智能优化控制.E-mail:zhlulu1991@163.com

    乔俊飞  北京工业大学信息学部教授.主要研究方向为城市污水处理过程智能优化控制, 神经网络结构设计与优化.E-mail:junfeq@bjut.edu.cn

    通讯作者:

    韩红桂  北京工业大学信息学部教授.主要研究方向为城市污水处理过程智能优化控制, 神经网络结构设计与优化.本文通信作者.E-mail:rechardhan@bjut.edu.cn

Identification and Suppression of Abnormal Conditions in Municipal Wastewater Treatment Process

Funds: 

National Natural Science Foundation of China 61533002

Scientific Research Foundation for China Mobile, Ministry of Education of China MCM2017030

National Natural Science Foundation of China 61622301

Beijing Natural Science Foundation 4172005

More Information
    Author Bio:

     Ph. D. candidate at the Faculty of Information Technology, Beijing University of Technology. He received his master degree in control science and engineering from Beijing University of Technology in 2012. His main research interest is intelligent self-organizing control of wastewater treatment process

     Ph. D. candidate at the Faculty of Information Technology, Beijing University of Technology. She received her bachelor degree in control science and engineering from Heze University in 2014. Her main research interest is multi-objective intelligent control of wastewater treatment process

     Professor at the Faculty of Information Technology, Beijing University of Technology. His research interest covers intelligent control of wastewater treatment process, structure design, and optimization of neural networks

    Corresponding author: HAN Hong-Gui  Professor at the Faculty of Information Technology, Beijing University of Technology. His research interest covers intelligent control of wastewater treatment process, structure design and optimization of neural networks. Corresponding author of this paper
  • 摘要: 城市污水处理过程(Municipal wastewater treatment processes,WWTPs)由于进水流量、进水成分、污染物种类、有机物浓度等被动接受,系统始终运行在非平稳状态,导致污泥膨胀等异常工况频发.异常工况一旦发生,会降低污水处理效率,引起出水水质超标等问题,严重时造成污水处理过程崩溃,引发事故.因此,如何降低异常工况发生率、保证城市污水处理过程安全平稳运行,是城市污水处理过程亟待解决的难题.围绕城市污水处理过程异常工况的识别和抑制方法,文中梳理了其研究进展.首先,介绍了城市污水处理运行的背景与异常工况的特点;其次,概述了一些主流的污水处理异常工况识别和抑制方法;最后,进行了分析与总结,指出了城市污水处理过程异常工况识别和抑制方法未来的研究方向.
    1)  本文责任编委 孙健
  • 图  1  污水处理异常

    Fig.  1  The data-driven method of abnormal conditions for wastewater treatment plant

    图  2  污水处理异常工况的抑制方法

    Fig.  2  The suppression method of abnormal conditions for wastewater treatment plant

    图  3  面向污水处理异常工况的识别和异常方法的研究

    Fig.  3  Study of identification and suppression of abnormal conditions for wastewater treatment plant

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  • 收稿日期:  2018-06-21
  • 录用日期:  2018-10-06
  • 刊出日期:  2018-11-20

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