Research on Dissolved Ozygen Classification based-on Image Processing and Neural Network
Dissolved Oxygen (DO) is one of the most important parameters describing biochemical process in wastewater treatment. It is usually measured with dissolved oxygen meters, and currently galvanic and polarographic electrodes are the predominant methods. Expensive, membrane surface inactivation, and especially need of cleaning and calibrating very frequently are common disadvantages of electrode-type measuring sensors. In our work, a novel method for classifying and further measuring dissolved oxygen based-on image processing and artificial neural network was researched. Pictures of the water-body surface in aeration basins are captured and transformed into HSI space data. These data plus the correspondent measured DO values are processed with a neural network. Using the well-trained neural network, a satisfied result for classifying dissolved oxygen according to the water-body pictures has been realized.
Dissolved Ozygen Image Processing Neural Network and Wastewater Treatment
Liu Liping Yu Naigong Sun Jinsheng
School of Electronic Information & Control Engineering Beijing University of Technology Beijing 1001 School of Electronic Information & Control Engineering Beijing University of Technology Beijing 1001 School of Information Engineering Hebei Polytechnic University Tangshan,Hebei 063009,China
国际会议
2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)
北京
英文
3377-3381
2009-08-16（万方平台首次上网日期，不代表论文的发表时间）