Electric arc furnace is widely used in the smelting industry

1 Introduction Electric arc furnaces are widely used in the smelting industry. It is powered by a three-phase alternating current of a special transformer. The three-phase alternating current directly heats the metal in the furnace through three electrodes that move up and down. In the smelting process, the electrical load of the three-phase AC arc furnace is unstable and asymmetrical. Especially in the melting period, due to unstable arc combustion, arcing, short circuit and block movement often occur, resulting in serious load failure. Symmetry; when the electric furnace is running, the improper adjustment of the electrode regulator or other artificial causes will cause the three-phase current of the electric arc furnace to be asymmetrical. Therefore, the electric arc furnace is a nonlinear time-varying system with very serious random disturbance, and its three-phase current balance. And the stability of the temperature is difficult to control.

Although the traditional control method is robust to the disturbance of system parameters, traditional control and single intelligent control are difficult to achieve good control effects due to the nonlinearity of the arc furnace control object and the time variation of the model parameters. To this end, we have developed a hierarchical control system for intelligent high-power electric arc furnaces, which has achieved good results in the practical application of lead-zinc smelting in Guangdong Province.

High-power arc furnace temperature and electrode current balance hierarchical intelligent control integrated control system is mainly divided into organization level (fuzzy expert control system in the figure), coordination level (composed of electrode current integration optimization and three-phase current balance) and execution level ( The electrode control device performs hierarchical intelligent control control. The hierarchical intelligent control control system covers the whole production process of the lead-zinc smelting electric heating front bed. The relationship between them is as follows: U is the input signal in the figure, U={u Represents the slag type selected signal, u represents the electrode position feedback signal represents the current feedback signal, f is the online feedback signal from the execution stage to the coordination stage (furnace temperature feedback signal), and f is the offline feedback signal from the coordination level to the organization level. The organization level produces current signals, temperature control signals and corresponding operational indications that meet the requirements of the production process coordination level, and further for the coordination level of the electrode three-phase current balance integrated power system and its automation. 1 This article was received on November 25, 2002. The control provides optimized command current information; the coordination stage accepts the command current and provides the switch control signal to the execution stage according to the feedback information of the three-phase current; the execution stage accepts the switch control signal of the coordination stage, and the three motors respectively drag The three-phase electrodes of the electric arc furnace change their relative positions in the slag to adjust the electrode current, so that the three-phase current is balanced and consistently directed toward the command current, thereby forming a furnace temperature that meets the requirements of the production process.

3 Hierarchical Intelligent Control System Implementation The implementation of the system is accomplished by three levels of independent and coordinated.

3.1 Organization-level implementation First, obtain prior knowledge from a large amount of previous production information, complete the initial setting of the fuzzy expert system, as the loading information of the system reset at the beginning of each phase: 1) establish the slag type, furnace temperature and maintain the temperature The relationship between the current values ​​required for constant, the principle of reasoning is that the current increases with the increase of the furnace temperature and the slag type variation. According to the seven grades of the slag type, the furnace temperature ranges from 1000 to 1350 ° C, and the corresponding current range 1800 ~ 4200A; 2) Establish a relationship between the slag type and the target value of the optimum furnace temperature for separation of lead and slag, and the relationship between the slag type and the optimal target value of the slag retention. 3) Establish a table of relationship between electrode position, current and slag surface. The electrode position L slag height H can be obtained by the expression H=L kI; the implementation of current organization and temperature organization of the fuzzy expert system is described below.

The current and electrode position signals continuously measured by the system during the entire EAF smelting production process, that is, the slag surface height is monitored indirectly. When the slag surface height increases rapidly, it means that the electric arc furnace slag control system enters the temperature control phase, and the optimum furnace temperature value corresponding to the set slag separation corresponding to the set slag type is taken out from the initialization table, and the temperature corresponding to the temperature Current values ​​and use them as target values ​​for temperature organization and current organization.

The current organization is derived by the fuzzy expert control system. The expert system gives a reasonable current target value for the current organization, and then the two-dimensional fuzzy rule infers the offset between the current organization and the target current value. The difference between the actual furnace temperature and the furnace temperature target value ET, the furnace temperature change trend and the control amount current organization offset E is defined as follows: and the fuzzy set of E is: the fuzzy control rule can be blurred with the following 35 Conditional statements to describe. The output control quantity of the fuzzy inference, that is, the current deviation value E, is added to the current target value, and the sum is the required current organization signal.

The temperature organization must meet the constraints of the process requirements. At the same time, as the input of the temperature-current model identified by the artificial neural network, in order to avoid the excessive output of the neural network due to input mutation, the temperature organization must be constrained to define the temperature organization T. It is expressed by the following formula: T is the furnace temperature at the time of slag introduction; it is the error value of the target furnace temperature T and T; t is counted from zero at the start of the slag temperature adjustment; it is the temperature organization change rate controlled by the expert system, The adjustment principle of t is to decrease when the temperature difference is large and the current is large; the above formula not only ensures that the temperature organization moves toward the target temperature direction, but also automatically adjusts the rate of change of the temperature organization according to the current magnitude.

When the slag surface drops rapidly, it means that the electric arc furnace slag discharge control system enters the heat preservation control stage, and the optimal furnace temperature value corresponding to the set slag type and the current value corresponding to the temperature are taken out from the initialization table, and They serve as new target values ​​for temperature organization and current organization. For the same reason, the fuzzy expert system completes the control of current organization and temperature organization at this stage, and thus achieves control of a complete production organization.

3.2 Coordination level implementation This level is mainly to complete the current optimization. The current optimization decision system mainly adopts the following measures: 1) The decision-making system shields the current-assisted organization output by the artificial neural network at the time of slag or slag discharge, and unblocks when the current-assisted organization enters the power supply capability of the transformer.

2) Other smelting period optimization decision system weights current organization and current assisted organization according to the following formula: command current 3) constant temperature lead slag separation stage After the timer expires, the process requires the system to stop supplying power, so as to reduce lead boiling and improve separation effect. The decision system simultaneously shields current assisted tissue and current organization.

4) Once the furnace temperature drops to the set critical temperature during the power outage period, the optimization decision system first turns on the output of the current organization and determines whether the current assisted tissue is shielded.

At the same time, current optimization is realized by expert fuzzy decoupling intelligent control and current expert decoupling control.

Expert fuzzy decoupling intelligent control is a summary of the skilled workers' operational experience. It uses a large amount of qualitative prior knowledge to establish fuzzy, inferential, logical rule bases and reasoning methods, which are realized under the conditions of integrated process and on-site environment. The weakening coupling of the three-phase electrode current, and fuzzy control of the expert optimization result by the fuzzy controller, the adjustment time of the three motors is obtained, which determines the position change of the three electrodes; the system control performance in turn affects the expert controller The expert decoupling rules are optimized, and the quantization factors of the fuzzy controller are reasonably corrected. The input of the expert fuzzy decoupling regulator is the three-phase current balance given value, and the output is the adjustment amount of the three electrode lifts. The three-phase current balance control is realized by adjusting the three electrodes. The structure of the expert fuzzy decoupling current regulator is shown in Figure 2.

The expert fuzzy decoupling control variable set is as follows: A phase current deviation amount Eia: B phase current deviation amount Eib: C phase current deviation amount Eic: A phase current deviation amount change rate $Eia: B phase current deviation amount change rate $Eib: C-phase current deviation rate change rate $Eic: No. 1 motor adjustment amount U1: No. 2 motor adjustment amount U2: No. 3 motor adjustment amount U3: Phase current deviation and deviation change rate; Ke, Kc are fuzzy controller systems The error and the quantization factor of the error rate of change; v1, v2, and v3 are respectively the motor adjustment time after quantization; three motor motion states; the motor regulation state -1 represents inversion, 0 represents stop, and 1 represents forward transmission.

The current expert decoupling control divides the three-phase current deviation into five current deviation sets NM, NS, 0, PS, PM according to the actual deviation eia, eib, eic of the three-phase current, according to expert experience, can be summarized The three-phase current and the positional relationship of the three electrodes can weaken the coupling relationship of the three-phase current. The following rules can be summarized: the coupling between the three-phase currents is weakened by the expert decoupling rule, and the phases are respectively A, B, and C. The current is controlled by the fuzzy controller to achieve current balance and optimization, so that the adjustment time of the three motors is obtained separately.

3.3 Execution Level Control The main goal of the implementation level is to control the electrode position based on the optimized current output from the coordination stage, so that the furnace temperature is optimally controlled, specifically by entropy theory. To this end, the design problem of the control system is represented by probability, and a distribution function indicating the optimal solution uncertainty within the allowable control space is specified. When the distribution satisfies Jayne's maximum entropy criterion, the performance criteria for the control problem are related to the entropy of choosing a certain control. An optimal control solution is obtained by deriving the minimum value of the entropy of the average performance of the system. To get the best control of the furnace temperature, the average value of the system's Lagrangian function L(x, u, t) takes the following form: indicates the system state space, u indicates the input control amount (current), and t indicates the control time. L>0, subject to the differential constraints determined by the following basic processes: M is a cluster within 8. When u, the design uncertainty density is selected in the allowable control space to satisfy the Jayne maximum entropy principle, and the relevant entropy is as follows: where: S represents entropy and T represents furnace temperature.

The optimal control then satisfies the following equation: then the problem becomes the minimum uncertainty in the selection of the optimal control within the allowable control space 8. Covered by the density function to reach the maximum. As long as the following formula is solved, the calculation result can be substituted into the formula, and the most effective control of the furnace temperature and the electrode position can be obtained.

4 Conclusion After the successful development of the device, the laboratory performance simulation test was carried out and put into use in the first and second systems of Shaoguan Smelter in Guangdong. The results show that the system is accurate, the control is fast and sensitive, and all functions can operate normally. In various harsh environments, the device operates well and has high reliability. It can ensure the smooth adjustment of the electrode, meet the requirements of the arc furnace temperature and the balance of the three-phase current, improve the labor intensity, reduce the power consumption, and improve the quality, output and management level of the lead-zinc smelting of the electric arc furnace.