| The pellets have small and uniform particle sizes and high reducibility,which are the main raw materials for steel smelting.The grate is an important part of equipment for drying and preheating pellets.It is composed of the up-draught drying zone(UDD),the down-draught drying zone(DDD),the preheating zone I(TPH ?),and the preheating zone II(TPH ?).Its internal space temperature field affects the drying and preheating effect of the pellets.Among them,the temperature field in the TPH directly affects the quality indicators such as the compressive strength and the oxidation rate of the pellets.The temperature field of the preheating zone of the pellets grate has the characteristics of multi-variable,coupling,nonlinear,and time-varying like other complex systems,so it is difficult to achieve precise control.The traditional PID control strategy is not ideal for complex system control and cannot meet accuracy requirements.The temperature field in the preheating zone of the grate is required to be balanced and stable.This paper considers the temperature field in the preheating zone of the grate as the research object and explores the control method for equilibrium and stability.The research results are of great significance for improving the quality of pellet preheating and prolonging the service life of the grate.The main content and research results include:1.Based on the theories of heat transfer,computational fluid dynamics,and porous media,a mathematical model of the spatiotemporally coupled temperature field in the preheating zone of the pellets grate is established,and the overall distribution of the temperature field is simulated and characterized by Ansys Fluent software.The four points of the spatial distribution characteristics of the temperature field in TPH I and TPH II change with time under the influence of the air velocity field and the air pressure field.The results show that the most important factor affecting the temperature field in the preheating zone is the inlet air temperature.The air velocity field and the air pressure field have the same change trend with time,and the gap area between TPH I and TPH II produce a coupling effect.Comprehensive consideration of the main influencing factors of the temperature field in the preheating zone provides a theoretical basis for control system modeling and control strategy design.2.A Bayesian-BP neural network system identification modeling method is proposed.The intake air temperature and outlet flow rate of TPH I and TPH II are taken as the system input,and the expected temperature value of the TPH temperature field is taken as the system output,the multi-control source system model of the temperature field in the preheating zone of the grate is established from data of the system input and output.The MATLAB software is used to simulate and analyze the fitting effects of different identification models of the multi-control source systems.The results show that the multi-control source system model of the TPH temperature field of the grate based on the Bayes-BP neural network system identification is more accurate and reliable.The final prediction error is 1.69 K,and the model fitting rate R is 99.98%.It provides a referenceable model for the balanced and stable control to the temperature field in the preheating zone.3.Given the complexity of the spatiotemporal coupling temperature field control of TPH I and TPH II,a fuzzy and feedforward compensation decoupling coordinated control strategy for the temperature field of the preheating zone of the grate is proposed.Based on the Simulink platform,the coordinated control system for the temperature field in the preheating zone of the grate is established and simulation studies of different control strategies are carried out.The dynamic and static performance of the system and the decoupling control effect under different control strategies are also compared and analyzed.The results indicate that the temperature field cooperative control system of the preheating zone based on the fuzzy and feedforward compensation decoupling control strategy has good dynamic and static performance.The temperature overshoot is controlled within 2.0%,and the steady-state error of the system is controlled within the allowable range,which is [-20 K,20K].The design of the decoupling link realizes the independence and relevance of two temperature fields control of TPH I and TPH II and has good adaptability and anti-interference ability.4.Based on the multi-physics measurement and control experimental equipment,a test device for the coordinated control system of the spatiotemporal coupling temperature field in the preheating zone of the pellets grate is constructed.Based on the LabVIEW platform,the monitoring software of the temperature field in the preheating zone is designed,and the related control algorithms and programs are written in combination with MATLAB software.The experiment has analyzed the accuracy of the Bayes-BP neural network online identification,the performance indicators of the preheating temperature field cooperative control system under fuzzy and feedforward compensation decoupling control.The results demonstrate that the prediction relative error of the multi-control source system model identified by Bayes-BP neural network online does not exceed 4%;The steady-state error of TPH I and TPH II temperature fields under fuzzy and feedforward compensation decoupling control strategy is 19 K and 6K respectively,and the temperature overshoot is 3.4% and 0.6% respectively.The experiment verifies that the temperature field cooperative control system of the preheating zone has good stability,accuracy,rapidity,and robustness.The research results of this paper provide an accurate and reliable referenceable model for the multi-variable coupled complex control system and put forward an effective decoupling control strategy for the coordinated control of the spatiotemporal coupling temperature field in the preheating zone of the pellets grate,which is suitable for similar industrial control occasions. |
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