Optimization of coagulant dosing process in water purification system

In the water purification plant, chemicals are injected for quick purification of raw water. The amount of chemicals intrinsically depends on the water quality such as turbidity, temperature, pH and alkalinity, etc. This paper presents the method of deriving the optimum dosing rate of coagulant in water purification system. A fuzzy model for normal condition and a neural network model for abnormal condition are developed for coagulant dosing and purifying process. The optimum coagulant dosing rate can be derived from the fuzzy model or the neural network model. Conventionally, four input variables (turbidity, temperature, pH, alkalinity of raw water) are known to be related to the process. Also, in order to consider the variation of algae, the variation of pH is regarded as a new input variable. The ability of the proposed control scheme validated through the field test is proved to be of considerable practical value