Data-driven intelligent monitoring system for key variables in wastewater treatment process  

作　　者：Honggui Han Shuguang Zhu Junfei Qiao Min Guo 

机构地区：[1]College of Electronic Information & Control Engineering Beijing University of Technology, Beijing 100124, China [2]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, China [3]Engineering Research Center of Digital Community, Ministry of Education, Beijing 100124, China [4]Beijing Laboratory for Urban Mass Transit, Beijing 100124, China

出　　处：《Chinese Journal of Chemical Engineering》2018年第10期2093-2101,共9页中国化学工程学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China(61622301,61533002);Beijing Natural Science Foundation(4172005);Major National Science and Technology Project(2017ZX07104)

摘　　要：In wastewater treatment process(WWTP), the accurate and real-time monitoring values of key variables are crucial for the operational strategies. However, most of the existing methods have difficulty in obtaining the real-time values of some key variables in the process. In order to handle this issue, a data-driven intelligent monitoring system, using the soft sensor technique and data distribution service, is developed to monitor the concentrations of effluent total phosphorous(TP) and ammonia nitrogen(NH_4-N). In this intelligent monitoring system, a fuzzy neural network(FNN) is applied for designing the soft sensor model, and a principal component analysis(PCA) method is used to select the input variables of the soft sensor model. Moreover, data transfer software is exploited to insert the soft sensor technique to the supervisory control and data acquisition(SCADA) system. Finally, this proposed intelligent monitoring system is tested in several real plants to demonstrate the reliability and effectiveness of the monitoring performance.In wastewater treatment process（WWTP）, the accurate and real-time monitoring values of key variables are crucial for the operational strategies. However, most of the existing methods have difficulty in obtaining the real-time values of some key variables in the process. In order to handle this issue, a data-driven intelligent monitoring system, using the soft sensor technique and data distribution service, is developed to monitor the concentrations of effluent total phosphorous（TP） and ammonia nitrogen（NH4-N）. In this intelligent monitoring system, a fuzzy neural network（FNN） is applied for designing the soft sensor model, and a principal component analysis（PCA） method is used to select the input variables of the soft sensor model. Moreover, data transfer software is exploited to insert the soft sensor technique to the supervisory control and data acquisition（SCADA） system. Finally, this proposed intelligent monitoring system is tested in several real plants to demonstrate the reliability and effectiveness of the monitoring performance.

关 键 词：DATA-DRIVEN Soft sensor Intelligent monitoring system Data distribution service Wastewater treatment process 

分 类 号：X703[环境科学与工程—环境工程]