Neural network prediction and control model for ammonia oxidizing process under low DO concentration
FENG Hong-li1, LIU Xiu-hong2, YANG Qing1, HUANG Si-ting1, CUI Bin1, ZHOU Tong1, YANG Yu-bing1, ZHOU Xue-yang1
1. Key Laboratory of Beijing Water Quality Science and Water Environment Recovery Engineering, Beijing University of Technology, Beijing 100022;
2. School of Environment & Natural Resources, Renmin University of China, Beijing 100872
Under low dissolved oxygen (DO) concentration, the neural network prediction method was applied in SBR for treating domestic wastewater. The neural network control model was built to predict and control the ammonia oxidizing process. The model was divided into two parts. In the first part with the correlation coefficient (R value) of 0.9985, the end of ammonia oxidization was predicted based on the on-line pH variations. In the second part with R value of 0.9083, the ammonia concentration was real-time predicted based on the on-line pH variations. The results showed that the model with high prediction accuracy, good controllability, better adaptability and stability, can not only benefit for achieving and stabilizing short-cut, but also promote the application of anaerobic ammonium oxidation for treating domestic wastewater.
冯红利, 刘秀红, 杨庆, 黄斯婷, 崔斌, 周桐, 杨玉兵, 周薛扬. 低溶解氧下氨氧化过程神经网络预测控制模型[J]. 中国环境科学, 2017, 37(1): 139-145.
FENG Hong-li, LIU Xiu-hong, YANG Qing, HUANG Si-ting, CUI Bin, ZHOU Tong, YANG Yu-bing, ZHOU Xue-yang. Neural network prediction and control model for ammonia oxidizing process under low DO concentration. CHINA ENVIRONMENTAL SCIENCECE, 2017, 37(1): 139-145.
Hellinga C,Schellen A A J C,Mulder J W,et al.The SHARON process:An innovative method for nitrogen removal from ammonium-rich wastewater[J].Water Science&Technology,1998,37(9):135-142.
[2]
Chung J W,Bae W.Nitrite reduction by a mixed culture under conditions relevant to shortcut biological nitrogen removal[J].Biodegradation,2002,13(3):163-170.
[3]
Peng Y Z,Zhu G B.Biological nitrogen removal with nitrification and denitrification via nitrite pathway[J].Applied Microbiology&Biotechnology,2006,73(1):15-26.
Aslan S,Miller L,Dahab M.Ammonium oxidation via nitrite accumulation under limited oxygen concentration in sequencing batch reactors[J].Bioresource Technology,2009,100(2):59-664.
Wang W L,Ren M,Guan Q.Soft-sensing method for wastewater treatment based on BP neural network[C]//Proc.of the 4th World Congress on Intelligent Control and Automation.上海:同济大学出版社,2002:2330-2332.
Li J P,Elliott D.Nielsen M,et al.Long-term partial nitrification in an intermittently aerated sequencing batch reactor (SBR) treating ammonium-rich wastewater under controlled oxygen-limited conditions[J].Biochemical Engineering Journal,2011,55(3):215-222.
[14]
Liu G Q,Wang J M.Long-term low DO enriches and shifts nitrifier community in activated sludge[J].Environmental Science Technology,2013,47(10):5109-5117.
Yang Q,Peng Y Z,Liu X H,et al.Nitrogen removal via nitrite form municipal wastewater at low temperatures using real-time control to optimize nitrifying communities[J].Environment Science Technology,2007,41(23):8159-8164.
Ruiz G,Jeison D,Chamy R.Nitrification with high nitrite accumulation for the treatment of wastewater with high ammonia concentration[J].Water Research,2003,37(1):1371-1377.
[19]
Xue Y,Yang F L,Liu S T,et al.The influence of control factors on the start up and operation for partial nitrification in membrane bioreactor[J].Bioresource Technology,2009,100(3):1055-1060.
[20]
Munoz C,Rojas D,Candia O,et al.Supervisory control system to enhance partial nitrification in an activated sludge reactor[J].Chemical Engineering Journal,2009,145(3):453-460.
Du Y,Peng Y Z,Cao S B,et al.Advanced nitrogen removal with simultaneous Anammox and denitrification in sequencing batch reactor[J].Bioresource Technology,2014,162(6):316-322.