An Ammonia Nitrogen Concentration Online Soft Measure Method based on the Neural Network
作者单位：School of Electrical and Electronics EngineeringShijiazhuang Tiedao University
会议名称：《第36届中国控制会议》
主办单位：Dalian University of Technology;Systems Engineering Society of China (SESC);Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA)
会议日期：2017年
学科分类：12[管理学] 082803[工学-农业生物环境与能源工程] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0828[工学-农业工程] 0804[工学-仪器科学与技术] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by National Natural Science Foundation of China under Grant 51674169 National Training Program of Innovation and Entrepreneurship for Undergraduates under Grant 201610107064
关 键 词：neural network wastewater treatment soft-sensor ammonia nitrogen concentration
摘 要：Aiming at the problem that the key water quality parameters in wastewater treatment processing is difficult to detect real-time *** ammonia nitrogen concentration soft measure model based on the artificial neural network（ANN） is proposed in this paper,and utilizing existing data to achieve parameters detection in real-time accurately during the process of wastewater treatment ***,parameters which are easily to detect are chosen as instrumental variables,then optimize the network’s parameters by gradient descent *** experimental results show that the fitting results of the effluent ammonia nitrogen in this paper is good when the hidden neurons are 15 and the learning rate is 0.07,which achieves the detection of the effluent ammonia nitrogen in real-time accurately.