电化学（中英文）2023，Vol.29Issue(12)：31-40,10.DOI:10.13208/j.electrochem.211215
基于BP神经网络的电化学还原硝酸盐过程智能控制
Intelligent Control Based on BP Artificial Neural Network for Electrochemical Nitrate Removal
摘要
Abstract
Achieving effective control of parameters in the process of nitrate wastewater treatment is critical to electrochemical water treatment.The powerful nonlinear mapping ability,self-adaptation and self-learning ability of neural network technology can optimize the electrochemical processing.However,there are few researches in this direction.Hence,based on the test data of the electrochemical reduction of nitrate,an electrochemical prediction model was established by using the BP neural network algorithm.Considering the correlation of various parameters in the electrochemical process,the reaction time,initial nitrate nitrogen concentration,pH and current density were determined as the input layer of the BP neural network for model establishment.Results showed that the optimal network configuration of 4-7-1 was achieved by optimizing the hyperparameters of hidden layers number,and the numbers of neurons and epochs.The predicted value of nitrate nitrogen concentration was consistent with the measured value,and the R2 value of 0.9095 was obtained.Meanwhile,the model predicted the effects of initial concentration,pH and current density on the removal efficiency of nitrate nitrogen.In the weak alkaline environment,the stability and reliability of nitrate electroreduction were higher than those in acidic and alkaline environments,and the predicted value of nitrate nitrogen was highly correlated to the true value(R2=0.9908).The initial concentration was negatively correlated to the removal rate,while the current density was positively correlated.Finally,the neural network model was used to control the electrochemical nitrate reduction process.Energy consumption tests were designed by optimizing current density,and 15％ reduction energy consumption was obtained within the same processing time and processing efficiency.Also,through the prediction model,the effluent quality can be guaranteed by timely adjusting the parameter in the case of sudden water quality changes.The research results can provide a reference for the intelligent control in the electrochemical removal of nitrate.At the same time,combining the understanding of the electrochemical treatment system and artificial intelligence technology,several ideas are proposed for the application of artificial intelligence technology in the field of electrochemical water treatment.关键词
硝态氮/电化学还原/BP神经网络/预测模型/智能控制Key words
Nitrate nitrogen/Electrochemical reduction/BPNN/Prediction model/Intelligent control引用本文复制引用
张芯婉,孟广源,方立强,常定明,李童,胡锦文,陈鹏,刘勇弟,张乐华..基于BP神经网络的电化学还原硝酸盐过程智能控制[J].电化学（中英文）,2023,29(12):31-40,10.基金项目
国家重点研发计划(No.2019YFC0408202)、国家自然科学基金(No.21876050)资助 （No.2019YFC0408202）
