Optimization System of Digistion and Precipitation Process in Alumina Refinery
|Course||Computer Science and Technology|
|Keywords||Automatic control Artificial Intelligence Industrial real-time database Data Mining|
Now three high and one low ( high energy consumption , high pollution , high investment, low efficiency ) requirements due to the rapid development of automatic control and information technology and the increasingly fierce competition in the commercial , industrial enterprises must improve the level of control and precision in the national energy conservation protection on the basis of the requirements of orderly and smooth industrial production , and reduce energy consumption . China Aluminum branch existing alumina dissolution - settlement process control system is no longer able to meet the industrial control requirements , the system regardless of a large PLC or DCS as a central control system , control strategy can only be based on the real-time production data collection judgment to adjust the parameters by writing curing interlock conditions , the control system more rigid . Due to the control of the dissolution - settlement \The same time as many of the key parameters of the factories during the industrial control , the detection level of technological development constraints most systems can not be timely and accurate measurement and analysis , some of the key control of the entire production line is still in the adjustment of status under the human experience , the technical and economic indicators control depends entirely on the actual experience of operating workers , the arbitrary dissolution process to achieve stable and high yield , and economic operation of volatility is very difficult . The system is designed mainly to today 's advanced control method - industrial control technology , artificial intelligence technology and industrial combining real-time database . Improve the scientific and technological means to optimize the control means to strengthen the means of measurement , acquisition of existing production plant DCS system monitoring data , and control of the operation, management and maintenance of the testing equipment , with laboratory production information network for real-time data exchange , and the use of advanced artificial intelligent reasoning techniques and data mining techniques to fault diagnosis system , parameters forecasting , auxiliary process optimization and production workshop in order to enhance the the intelligent production capacity and information management capabilities .