Open AccessIntelligent Control System Based on Artificial Neural Network Applied research in autotrophic nitrogen removal process
Author(s) -
Sijie He,
Longqing Tang,
Yuanxin Liu,
Ximei He,
Jia Chen,
Xin Wen
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/770/1/012036
Subject(s) - artificial neural network , autotroph , process (computing) , environmental science , nitrogen , inflow , process engineering , computer science , pulp and paper industry , chemistry , engineering , artificial intelligence , genetics , organic chemistry , bacteria , biology , operating system , physics , mechanics
In view of the difficulty in controlling the stable operation of autotrophic nitrogen removal system, this study plans to design a DO intelligent control system based on artificial neural network control, which can intelligently and accurately control dissolved oxygen in liquid phase according to the water inflow and operation state of the system. Firstly, the autotrophic nitrogen removal system was constructed step by step, and the influence of dissolved oxygen with different concentrations was explored by using the characteristics of system microbes sensitive to dissolved oxygen. Then, the dissolved oxygen intelligent control system based on artificial neural network was developed. Finally, the operation mode of autotrophic nitrogen removal process optimized by the dissolved oxygen intelligent control system based on artificial neural network was explored and the key parameters of system operation were put forward. The single-stage autotrophic nitrogen removal system equipped with DO precise control system was tested by artificial simulated wastewater. Under various load conditions, the total nitrogen removal rate of the system was more than 86%, and the system was efficient and stable.