Data mining to support anaerobic WWTP monitoring

Control Engineering Practice(2007)

引用 17|浏览24
暂无评分
摘要
The stable and efficient operation of anaerobic wastewater treatment plants (WWTPs) is a major challenge for monitoring and control systems. Support for distributed anaerobic WWTPs through remotely monitoring their data was investigated in the TELEMAC framework. This paper describes how the accumulating filtered sensor data was mined to contribute to the refining of expert experience for insights into digester states. Visualisation techniques were used to present cluster analyses of digester states. A procedure for determining prediction intervals is described together with its application for volatile fatty acid concentrations; this procedure enables prediction risk assessment.
更多
查看译文
关键词
Water pollution,Waste treatment,Prediction interval,Reactor modelling,Reactor states,Water pollution,Waste treatment,Prediction interval,Reactor modelling,Reactor states
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要