Application of Intelligent Identification And Quality Online Prediction System for Sintering Conditions
Due to the harsh production environment of sintering process,high cost of online detection and low accuracy of online detection and other reasons,the working conditions and quality of the company's production process can only be obtained through offline detection and manual observation,resulting in failure to timely and effectively monitor production,adjust technology and improve quality.In order to solve the problems such as the difficulty in the identification of sintering conditions in the plant and the lag in the offline testing of sintering quality by subjective large machine,the multi-stage condition online judgment of sintering production process was realized through data and image processing,deep learning technology and multi-information fusion technology.The accuracy rate of system condition judgment was more than 90％,and the quality online prediction error was less than 95±5％.
sintering conditionsmonitor the production processsintered ore qualityonline detection
NETL
NSTL
万方数据
