工业水处理 ›› 2024, Vol. 44 ›› Issue (7): 190-196. doi: 10.19965/j.cnki.iwt.2023-1032

• 工程实例 • 上一篇    下一篇

AI人工智能加药技术在采煤废水重介速沉工艺中的应用

薛晓强1(), 李杰1, 贺高峰1, 王志慧2, 王艳兵2, 夏天飞2, 杨光3, 张亚宾3()   

  1. 1. 陕西小保当矿业有限公司, 陕西 榆林 719302
    2. 中煤(北京)环保股份有限公司, 北京 100293
    3. 北京标志卓信科技有限公司, 北京 101318
  • 收稿日期:2024-06-06 出版日期:2024-07-20 发布日期:2024-07-31
  • 作者简介:

    薛晓强(1984— ),本科,工程师。E-mail:

    张亚宾,本科,工程师。E-mail:

Application of AI artificial intelligence dosing technology in heavy medium rapid sedimentation process of coal mining wastewater

Xiaoqiang XUE1(), Jie LI1, Gaofeng HE1, Zhihui WANG2, Yanbing WANG2, Tianfei XIA2, Guang YANG3, Yabin ZHANG3()   

  1. 1. Shaanxi Xiaobaodang Mining Co. , Ltd. , Yulin 719302, China
    2. Zhongmei(Beijing) Environmental Protection Engineering Co. , Ltd. , Beijing 100293, China
    3. Beijing Biaozhi Zhuoxin Science & Technology Co. , Ltd. , Beijing 101318, China
  • Received:2024-06-06 Online:2024-07-20 Published:2024-07-31

摘要:

重介速沉工艺在煤矿采煤废水中应用广泛,其工艺特点是多变量、非线性和时变性。加药的精准程度影响重介速沉工艺出水指标和运行成本。AI人工智能软件作为一款数据科学工具,用数字技术取代了“传统人的经验和直觉”。与传统加药控制方式相比,采用AI人工智能加药系统,可以根据水量和水质,实时地精准调控加药量,保证出水水质平稳,可以实现提前对出水水质指标的预测。通过AI人工智能软件对现有重介速沉工艺进行数据分析,并寻找数据间的潜在关联,自主创建算法模型,并对其有效性进行验证,最终达到可用于指导生产的实验目的。在同样工控下对比,AI人工智能加药比传统加药节省药量13.5%,实现节能降耗;AI人工智能加药系统可以对连续增加的数据进行深度学习,不断自动校正模型参数,使控制更加精确。

关键词: AI人工智能加药, 采煤废水, 重介速沉, 精准加药

Abstract:

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.

Key words: AI artificial intelligence dosing, coal mining wastewater, heavy medium sedimentation, accurate dosing

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