A Study Of The Accuracy Control Of Gas Output And The Operation Efficiency Of The Air-Blower

The treatment process of modern sewage plants is dominated by biological treatment methods(also known as activated sludge methods).Aeration is an important part of biological treatment,and it is also the most energy-consuming part of sewage plants.Controlling of dissolved oxygen(DO)at 2mg / L can effectively improve the water quality of sewage treatment,while reducing aeration rate(i.e.the air-blower outgassing volume)and saving production costs.At present,many sewage plants in China have great fluctuations in DO,which is not conductive to the stability and efficiency of the sewage treatment.To fix this problem,it is necessary to accurately control aeration rate and maintain the concentration of DO at about 2 mg/L.This can not only meet the needs of production quality,but also minimize aeration rate and reduce energy consumption.In this article,we used BP neural network and the least squares method to obtain the analytical formula of the gas output when multiple air-blowers are parallel.Efficiency of air-blower under different working conditions is examined by analyzing the historical data,so that air-blower outgassing volume could achieve the maximum provided efficiency that is satisfied the production demand.A prediction model is established to control aeration rate by constantly adjusting the opening of the inlet guide vane of the air-blower.The results show that the prediction model has a short delay time,high precision,and compelling real-time control ability or air-blower outgassing volume,and achieves the purpose of intelligent control,real-time control,reducing energy consumption,improving efficiency,and saving operating costs,we expect this model has a wide range of applications in the automatic control of sewage treatment.