This invention relates to the field of
wastewater treatment technology, specifically to a dual-
loop control method for aerobic space-
aeration based on the
nitrification process in
wastewater treatment, constructing a
dual loop of "on-demand
aeration" and "on-demand aerobic"
aeration. In the aeration loop, a SAD (Self-
Aeration Optimization) method is proposed. n The indicator integrates
deep learning feedforward prediction and PID feedback correction with dead zone to precisely control
aeration rate directly with
ammonia nitrogen removal as the target; in the aerobic space loop, a SAD is established. n A U-shaped curve correlation model with aeration intensity is used to solve for the economic aeration intensity through a neural network, and the optimal aerobic zone volume is dynamically calculated in conjunction with the target
aeration rate. The two loops are decoupled and coordinated based on the
nitrification process, ensuring the
aeration system always operates at its optimal energy efficiency point. This invention achieves in-situ, zero-
delay, and precise control of the biological
nitrification process. While ensuring stable compliance with
effluent ammonia nitrogen standards, it significantly reduces aeration
energy consumption and the unit consumption of added carbon sources, improves
total nitrogen removal rate, and achieves energy saving, consumption reduction, and quality improvement in
wastewater treatment.