MLP, ANFIS, and GRNN based real-time coagulant dosage determination and accuracy comparison using full-scale data of a water treatment plant

2016 ◽  
Vol 66 (1) ◽  
pp. 49-61 ◽  
Author(s):  
Chan Moon Kim ◽  
Manukid Parnichkun
2000 ◽  
Vol 42 (3-4) ◽  
pp. 403-408 ◽  
Author(s):  
R.-F. Yu ◽  
S.-F. Kang ◽  
S.-L. Liaw ◽  
M.-c. Chen

Coagulant dosing is one of the major operation costs in water treatment plant, and conventional control of this process for most plants is generally determined by the jar test. However, this method can only provide periodic information and is difficult to apply to automatic control. This paper presents the feasibility of applying artificial neural network (ANN) to automatically control the coagulant dosing in water treatment plant. Five on-line monitoring variables including turbidity (NTUin), pH (pHin) and conductivity (Conin) in raw water, effluent turbidity (NTUout) of settling tank, and alum dosage (Dos) were used to build the coagulant dosing prediction model. Three methods including regression model, time series model and ANN models were used to predict alum dosage. According to the result of this study, the regression model performed a poor prediction on coagulant dosage. Both time-series and ANN models performed precise prediction results of dosage. The ANN model with ahead coagulant dosage performed the best prediction of alum dosage with a R2 of 0.97 (RMS=0.016), very low average predicted error of 0.75 mg/L of alum were also found in the ANN model. Consequently, the application of ANN model to control the coagulant dosing is feasible in water treatment.


2014 ◽  
Vol 71 (4) ◽  
pp. 638-644 ◽  
Author(s):  
Alina Pruss

A technological investigation was carried out over a period of 2 years to evaluate surface water treatment technology. The study was performed in Poland, in three stages. From November 2011 to July 2012, for the first stage, flow tests with a capacity of 0.1–1.5 m3/h were performed simultaneously in three types of technical installations differing by coagulation modules. The outcome of the first stage was the choice of the technology for further investigation. The second stage was performed between September 2012 and March 2013 on a full-scale water treatment plant. Three large technical installations, operated in parallel, were analysed: coagulation with sludge flotation, micro-sand ballasted coagulation with sedimentation, coagulation with sedimentation and sludge recirculation. The capacity of the installations ranged from 10 to 40 m3/h. The third stage was also performed in a full-scale water treatment plant and was aimed at optimising the selected technology. This article presents the results of the second stage of the full-scale investigation. The critical treatment process, for the analysed water, was the coagulation in an acidic environment (6.5 < pH < 7.0) carried out in a system with rapid mixing, a flocculation chamber, preliminary separation of coagulation products, and removal of residual suspended solids through filtration.


2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Benjamin Buysschaert ◽  
Lotte Vermijs ◽  
Agathi Naka ◽  
Nico Boon ◽  
Bart De Gusseme

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