The temperature field in MgO single crystal furnace is crucial to grow high-purity MgO single crystals with large sizes. In order to build proper temperature gradient, firstly finite element method (FEM) was used to...The temperature field in MgO single crystal furnace is crucial to grow high-purity MgO single crystals with large sizes. In order to build proper temperature gradient, firstly finite element method (FEM) was used to study the temperature field distributions, and then a temperature controller with adaptive neuro- fuzzy inference system (ANFIS) was developed based on the result of FEM and practical experiences. When the temperature in MgO single crystal furnace was changed, the controller would regulate the positions of three- phase electrodes and the voltage of the power simultaneously. The experimental results indicate that using the adaptive neuro-fuzzy control system can improve the quality and the quantity of the MgO single crystal production.展开更多
In order to improve the end-point hit rate of basic oxygen furnace steelmaking,a novel dynamic control model was proposed based on an improved twin support vector regression algorithm.The controlled objects were the e...In order to improve the end-point hit rate of basic oxygen furnace steelmaking,a novel dynamic control model was proposed based on an improved twin support vector regression algorithm.The controlled objects were the end-point carbon content and temperature.The proposed control model was established by using the low carbon steel samples collected from a steel plant,which consists of two prediction models,a preprocess model,two regulation units,a controller and a basic oxygen furnace.The test results of 100 heats show that the prediction models can achieve a double hit rate of 90%within the error bound of 0.005 wt.%C and 15℃.The preprocess model was used to predict an initial end-blow oxygen volume.However,the double hit rate of the carbon con tent and temperature only achieves 65%.Then,the oxygen volume and coolant additi ons were adjusted by the regulation units to improve the hit rate.Finally,the double hit rate after the regulation is reached up to 90%.The results indicate that the proposed dynamic control model is efficient to guide the real production for low carbon steel,and the modeling method is also suitable for the applications of other steel grades.展开更多
基金Funded by the National High-Tech R&D Program(Nos.2008AA03A325, 2011AA06103)
文摘The temperature field in MgO single crystal furnace is crucial to grow high-purity MgO single crystals with large sizes. In order to build proper temperature gradient, firstly finite element method (FEM) was used to study the temperature field distributions, and then a temperature controller with adaptive neuro- fuzzy inference system (ANFIS) was developed based on the result of FEM and practical experiences. When the temperature in MgO single crystal furnace was changed, the controller would regulate the positions of three- phase electrodes and the voltage of the power simultaneously. The experimental results indicate that using the adaptive neuro-fuzzy control system can improve the quality and the quantity of the MgO single crystal production.
基金This work was supported by Liaoning Province PhD Start-up Fund(No.201601291)Liaoning Province Ministry of Education Scientific Study Project(No.2O17LNQN11).
文摘In order to improve the end-point hit rate of basic oxygen furnace steelmaking,a novel dynamic control model was proposed based on an improved twin support vector regression algorithm.The controlled objects were the end-point carbon content and temperature.The proposed control model was established by using the low carbon steel samples collected from a steel plant,which consists of two prediction models,a preprocess model,two regulation units,a controller and a basic oxygen furnace.The test results of 100 heats show that the prediction models can achieve a double hit rate of 90%within the error bound of 0.005 wt.%C and 15℃.The preprocess model was used to predict an initial end-blow oxygen volume.However,the double hit rate of the carbon con tent and temperature only achieves 65%.Then,the oxygen volume and coolant additi ons were adjusted by the regulation units to improve the hit rate.Finally,the double hit rate after the regulation is reached up to 90%.The results indicate that the proposed dynamic control model is efficient to guide the real production for low carbon steel,and the modeling method is also suitable for the applications of other steel grades.