Sewage treatment effluent total phosphorus prediction method based on self-organization cascade neural network

Abstract

A sewage treatment effluent total phosphorus prediction method based on a self-organization cascade neural network belongs to the field of controls science and engineering and also belongs to the field of environmental science and engineering. In order to solve the problem that the real-time on-line measurement of the effluent total phosphorus cannot be achieved in the current city sewage treatment process, the invention achieves on-line real-time prediction of the effluent total phosphorus. The method designs the self-organization growth-type cascade network structure, a variable contribution rate calculation formula and a differentiation weight training method, and improves the effluent total phosphorus prediction precision in the city sewage treatment process by timely adjusting the structure and the connection weight of the cascade-correlation network. The experiment result shows that the intelligent prediction method can timely and accurately measure the effluent total phosphorus concentration in the city sewage treatment process. The invention adjusts correlated control links in the city sewage treatment process and materials in biochemical reactions, thereby improving the effluent quality of sewage treatment and providing theoretical support and technical support for improvement of safe and stable operation of the sewage treatment process.

Description

technical field [0001] The invention designs a method for predicting the total phosphorus in the effluent of the urban sewage treatment process based on the self-organized cascade neural network, and realizes the online prediction of the total phosphorus in the effluent. The real-time prediction of effluent total phosphorus is an important link to realize the optimal control of sewage treatment, an important basis for the normal operation of the sewage treatment process, and an important link to control environmental water pollution. It belongs to the field of control science and engineering, and also belongs to the field of environmental science and engineering. Background technique [0002] The national "Twelfth Five-Year Plan" pointed out that it is necessary to speed up the construction of urban sewage treatment and recycling facilities nationwide, promote the reduction of major pollutants, and improve the quality of water environment. By 2015, the overall goal of urban s...

AI Technical Summary

Problems solved by technology

The whole process takes a long time, the operation is complicated, the interference is large, the accuracy is not high, and it is difficult to meet the needs of fine control of the urban sewage treatment process

Moreover, there are potential safety hazards in some digestion processes, and the application in the actual sewage treatment process is limited.

At the same time, due to complex biochemical reactions and environmental uncertainties, the sewage treatment process is highly nonlinear and strongly coupled, making it difficult to establish an accurate mechanism model

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