A Feasible Data-Driven Mining System to Optimize Wastewater Treatment Process Design and Operation
作者： Yong Qiu , Ji Li , Xia Huang , Hanchang Shi
DOI: 10.3390/W10101342
关键词: Process engineering 、 Process (engineering) 、 Data collection 、 Data warehouse 、 Data-driven 、 Process design 、 Search algorithm 、 Quality (business) 、 Computer science 、 User interface
摘要: Achieving low costs and high efficiency in wastewater treatment plants (WWTPs) is a common challenge developing countries, although many optimizing tools on process design operation have been well established. A data-driven optimal strategy without the prerequisite of expensive instruments skilled engineers thus attractive practice. In this study, data mining system was implemented to optimize WWTPs China, following an integral procedure including collection cleaning, warehouse, mining, web user interface. warehouse demonstrated analyzed using one-year 30 China. Six sludge removal loading rates water quality indices, such as chemical oxygen demand (COD), total nitrogen (TN), phosphorous (TP), were calculated derived parameters organized into fact sheets. searching algorithm programmed find out five records most similar target scenario. interface developed for users input scenarios, view outputs, update database. Two case investigated verify system. The results indicated that effluent Case-1 WWTP improved meet discharging criteria through operations, Case-2 could be refined feedback loop. discussion gaps, potential, challenges practice provided. study good candidate understand control their processes WWTPs.
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