Soft Sensing Model of Underflow Concentration for Thickener Process based on Data Reconciliation
作者单位：School of Information Science and EngineeringNortheastern University State Key Laboratory of Synthetical Automation for Process IndustriesNortheastern University
会议名称：《第32届中国控制与决策会议》
会议日期：2020年
学科分类：081902[工学-矿物加工工程] 0819[工学-矿业工程] 080202[工学-机械电子工程] 08[工学] 0802[工学-机械工程]
关 键 词：Thickener soft sensing data reconciliation
摘 要：Measured data in industrial production inevitably contain stochastic errors that are influenced by the environment and equipment,and the stochastic errors will reduce the accuracy of the measured *** are widely used in mineral processing and sewage treatment,but the accuracy of the variables of the thickener process cannot meet the requirements,caused by the stochastic errors,and the underflow concentration cannot be real-time ***,pressure sensors were installed in the thickener to establish the soft sensing model of the underflow concentration,but the model accuracy is low owing to the stochastic errors of pressure *** paper presents a soft sensing model of underflow concentration based on data *** data reconciliation method is used to improve the accuracy of variables in thickener process,and then the soft sensing model of underflow concentration is established using the reconciled *** the data of impact thickener process,the validity of the model is confirmed.