Patent Document ID: 9747544
Application ID: 13985482
Patent Flag: 1

Claim One:
1. A method of wastewater treatment based on control of dissolved oxygen using a fuzzy neural network, the method comprising: measuring an inflow flowrate, an oxidation-reduction potential (ORP) value in an anaerobic tank corresponding to real-time aeration quantity, a dissolved oxygen (DO) value in an aerobic tank corresponding to real-time aeration quantity, an influent chemical oxygen demand (COD) value, and an actual effluent COD value in an anaerobic/oxic (A/O) wastewater treatment process; collecting the measured data, sending the data via a computer to a COD fuzzy neural network predictive model, and computing as physical quantities, so as to establish an effluent COD predicted value; obtaining an error and an error change rate of the effluent COD value; comparing the effluent COD predicted value with an effluent COD set value; determining an effluent COD error or change amount and an effluent COD error change rate; inputting the effluent COD error or change amount and the effluent COD error change rate as two input variables to a DO fuzzy neural network control model, and using the DO fuzzy neural network control model to determine a correction amount of aeration quantity, thus obtaining a corrected real-time aeration quantity; controlling an air blower to obtain a suitable dissolved oxygen concentration by a control system according to the corrected real-time aeration quantity; inputting the corrected aeration quantity as an input of the COD fuzzy neural network model; obtaining a second effluent COD predicted value using the COD fuzzy neural network predictive model using the corrected aeration quantity; and repeating the same steps recited above in subsequent cycles, thus providing a method of wastewater treatment based on control of dissolved oxygen using a fuzzy neural network using an on-line prediction and real-time control of dissolved oxygen in the wastewater treatment method.