摘要
在介绍序批式活性污泥法(SBR)的城市生活污水处理工艺的基础上,针对反应过程所具有的多变量、非线性和动态复杂反应的特点,利用水质参数与多个过程可测参数间的关联关系,提出了基于Elman递归人工神经网络的水质参数软测量模型.以ORP,DO浓度和pH值作为输入参数,可实现对COD,NH3,TP水质参数的软测量.基于污水处理实验数据建立软测量模型,结果表明,上述软测量模型对污水处理水质指标COD,NH3,TP具有理想的预测效果.
An Elman recursive neural network based water quality parameters soft sensing model is proposed for the sequential wastewater treatment processes,regarding the characteristics of multivariable,nonlinear,dynamic and complicated reactions in the treatment process,and utilizing the relationship between water quality parameters and the measurable process parameters.DO(dissolved oxygen), ORP(oxidation reduction potential) and pH are selected as input parameters,which can realize the soft sensing of the water qu...
出处
《东南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第S1期119-123,共5页
Journal of Southeast University：Natural Science Edition
关键词
污水处理
软测量
神经网络
wastewater treatment
soft sensing
neural network
