Abstract
Chemical sewage treatment are the main contents of the sewage treatment, It is a key factor in the influence and constraints of water environmental improvement. Its water quality control has been an important subject of research in the field of water treatment technology. In this paper, through understanding and research for the sewage treatment process both at home and abroad, water quality monitoring technology and treating processes automatic control technical aspect, artificial neural network forecasting the future of wastewater treatment technology is an important field of measurement and control the direction of development, for key water quality parameters can not be the issue of online monitoring in sewage treatment process.
In view of the characteristics of strongly nonlinear, large time-varying, a serious lag in the sewage treatment process,it is difficult to establish establish accurate mathematical models through the mechanism analysis. This paper uses modeling methods to identify based on dynamic neural network technology. The main contents contain the following three aspects:In this paper, the main contents contains the following two aspects:
1、Chemical sewage treatment works based on the actual method of data preprocessing.
From the on-site historical data in the the actual chemical sewage treatment plant, Combination of technology and data processing technology practice,research databases, error handling, data interpolation and restoration, such as data pre-processing, It provides a good basis for data for neural network modeling.
2、Research and the establishment of sewage treatment effluent quality artificial neural network prediction model.
The core of the sewage treatment system based on Elman Dynamic Neural Network - biochemical system's neural network forecast model, forecasts the sewage water leakage water quality by the ammonia nitrogen and COD density. Contrasting the basic Elman algorithm, and conducting the research and improvement from the algorithm and the network architecture two aspects, It proposes the improving Levenberg-Marquardt antipropagation algorithm and the Elman structure algorithm of the increasing forecast item′s history value of exports.
3、Simulation research for sewage water quality parameter forecast model.
Working on the water quality parameter forecast model using the MATLAB neural network toolbox the simulation research,The simulation results indicates that: Through the algorithm and the structure improvement, the established biochemical system neural network forecast model has the distinct enhancement in the precision and the training effectiveness, which also can forecast the water leakage ammonia nitrogen and the COD density well.
In a word,this research work actually unifies the artificial neural networks technology and the chemical industry sewage treatment project,and it has confirmed the neural network forecasting technology to apply in the sewage treatment process water leakage water quality parameter forecast feasibility from the theory and the simulation, for further realizing the water leakage water quality control to lay the solid foundation.