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污水处理工艺数据分析技术的现状与趋势

高嵩,  邱勇,  孟凡琳,  张夏颖,  盘德立,  王凯军

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文章导航 > 环境工程  > 2022 >  40(6): 194-203
高嵩, 邱勇, 孟凡琳, 张夏颖, 盘德立, 王凯军. 污水处理工艺数据分析技术的现状与趋势[J]. 环境工程, 2022, 40(6): 194-203. doi: 10.13205/j.hjgc.202206025
引用本文: 高嵩, 邱勇, 孟凡琳, 张夏颖, 盘德立, 王凯军. 污水处理工艺数据分析技术的现状与趋势[J]. 环境工程, 2022, 40(6): 194-203. doi: 10.13205/j.hjgc.202206025
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DONG Hao, SUN Lin, OUYANG Feng. PREDICTION OF PM2.5 CONCENTRATION BASED ON INFORMER[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(6): 48-54,62. doi: 10.13205/j.hjgc.202206006
Citation: GAO Song, QIU Yong, MENG Fanlin, ZHANG Xiaying, PAN Deli, WANG Kaijun. STATE-OF-ART AND TRENDS OF DATA ANALYTICAL TECHNIQUES FOR WASTEWATER TREATMENT PROCESSES[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(6): 194-203. doi: 10.13205/j.hjgc.202206025
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污水处理工艺数据分析技术的现状与趋势

doi: 10.13205/j.hjgc.202206025

  • 1. 江苏省(宜兴)环保产业技术研究院, 江苏 宜兴 214200;

  • 2. 清华大学 环境学院, 北京 100084

基金项目: 

国家重点研发计划项目"面向未来的创新型水技术研发、示范、转化平台建设及实践研究"(2017YFE0119400)

详细信息
    作者简介:

    高嵩(1980-),男,博士在读。主要研究方向为环保科技创新生态、环保创新创业体系、环保装备标准化体系构建、污水厂低碳智慧运营管理。gaosong@jiei.org.cn

    通讯作者:

    邱勇(1977-),男,博士,副研究员。主要研究方向为水处理工艺模拟、环境微流控、智慧水务。qiuyong@tsinghua.edu.cn

STATE-OF-ART AND TRENDS OF DATA ANALYTICAL TECHNIQUES FOR WASTEWATER TREATMENT PROCESSES

  • 1. Jiangsu (Yixing) Institute of Environmental Industry, Yixing 214200, China;

  • 2. School of Environment, Tsinghua Unversity, Beijing 100084, China

摘要

    摘要
  • 摘要: 数据科学的飞速发展为污水处理厂工艺数据分析提供了有力的技术工具。在污水处理工艺运行中应用数据分析技术,需要克服数据、算法和算力上的困难。介绍了污水处理工艺数据分析技术的发展现状,总结了其在数据质量和数学模型方面的技术难点,分析了污水处理工艺数据分析技术的4种典型应用场景,介绍了12个国内外数据分析集成应用的案例,评估了工艺数据分析技术的成熟度和行业应用的就绪度,讨论了技术的发展趋势。研究结果有助于污水处理系统运管人员掌握工艺数据分析技术进展和运用数据分析技术处理业务的需求。
    Abstract: The rapidly developing technologies in data science have provided powerful tools for the data analytical process in wastewater treatment plants (WWTPs).Successfully applying data analytics in WWTPs needs the systematical approach to overcome the gaps in data,algorithm,and computing power.In this paper,firstly we summarized the advances in data analytics for WWTPs,and discussed the challenges that remained in the data quality control and mathematical models.Secondly,we summarized four typical four scenarios of data analytics in WWTPs and introduced twelve cases of integral application of data analytics in the wastewater treatment systems.Thirdly,the technical maturity of data analytics in WWTPs was estimated using the classic tools of hyper curves and technical readiness levels.Finally,the demands of water sectors on data analytics were analyzed to clarify the trends of the technical evolution of data analytics for WWTPs.This review was expected to help the operators and managers in WWTPs understand the advances in data analytics and utilize the developed tools to solve the process problems.
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