Design of Online Control and Detection System for Wastewater Treatment Based on Adaptive Multi Objective Control Strategy

This article focuses on the current wastewater treatment process, which has many water quality targets. In order to meet the demand for environmental protection and energy conservation, the system energy consumption, including aeration process energy consumption and pump energy consumption, is integrated into the output target of the treatment model. A framework system for online control and monitoring of the wastewater treatment system is designed. Firstly, the functions of the entire system framework are described in detail according to the data processing and online monitoring scheme. Then, an adaptive intelligent wastewater parameter dynamic optimization model is constructed to address the problem of multiple target parameters in the wastewater treatment process. This article uses an improved particle swarm optimization algorithm to dynamically change the inertia weight of each target parameter, improve the global search ability of particles, and enhance Pareto The distribution and convergence of the solution, as well as the introduction of crowding distance sorting method, are used to maintain the external elite set and update the optimal global value, better maintaining the diversity and convergence of the population. At the same time, self-organizing optimization strategy is integrated into the model, and the detailed design process of the model is given. Finally, based on Matlab simulation model, the treatment effect of key sewage parameters and the prediction results of sewage treatment parameters under dynamic disturbance are analyzed, proving the effectiveness of the proposed method in this paper.