EP1596999B1 - Method for regulating the temperature of a metal strip, especially in a cooling path - Google Patents

Abstract

The invention relates to a method for controlling or regulating the temperature of a metal strip in a cooling path of a hot rolling system. A desired temperature gradient is compared to an actual temperature gradient in order to determine adjusting signals for the cooling path. At least one target function is formed for actuators of the cooling strip, taking into account auxiliary conditions, and said target function is solved as a quadratic optimization problem for the purpose of model predictive regulation. The invention also relates to an overlapping regulation for the finishing train and the cooling path of the hot rolling system.

Description

The invention relates to a method for controlling and / or regulating the temperature of a metal strip in a plant of the steel industry, in particular in a cooling section, according to the preamble of claim 1. Such a method is known from VS6185970 B.

From DE 199 63 186 A1 a control method for a cooling section is known, which is preceded by a finishing train for rolling of hot metal strip. In this control method, when the hot strip enters the cooling section, band points and their initial temperatures are detected and individual setpoint temperature profiles are assigned to the detected band points. The band points, their initial temperatures and their desired temperature curves are fed to a model for the cooling section. The band points are tracked as they pass through the cooling section. In the cooling section, the hot strip is subjected to temperature influencing by means of temperature influencing devices. The tracking and the temperature changes are also fed to the model. The model determines in real time expected actual temperatures of the recorded band points and assigns them to the band points. As a result, the temperature as a function of the strip thickness is available for each band point at any time. Furthermore, it determines control values for the temperature-influencing devices on the basis of the setpoint temperature profiles assigned to the detected band points and the expected actual temperatures, and supplies the control values to them. The temperature control is used in particular for targeted adjustment of material and structural properties of the metal hot strip. As a rule, the temperature control is carried out in such a way that a predetermined reel temperature curve is achieved as well as possible from the outlet of the cooling section.

Decisive for material and structural properties of the metal strip are, in addition to the chemical composition and parameters of the forming process, such as. the acceptance distribution over the stands of the finishing scale and the temporal temperature profile of the strip material as it passes through the plant.

The last actuators for the temperature profile of the metal strip within the system are usually located within the cooling section. In the cooling section, the phase transformation of the material often takes place. As actuators usually serve the valves of the cooling section. For certain cooling sections, such as Heavy plate mills, in addition, the mass flow, i. in particular, the belt speed, are provided.

The object of the present invention is to improve the control or the regulation of the temperature of a metal strip, in particular in a cooling section, in a plant of the steel industry in such a way that the disadvantages of known controls or regulations are largely avoided and the efficiency of the control or Control is increased.

The object is achieved by a method for controlling and / or regulating the temperature of a metal strip in a plant of the steel industry, in particular in a cooling section, which is arranged downstream of a rolling train for rolling metal heat, wherein for determining actuating signals a desired temperature profile with an actual Temperature characteristic is compared, and wherein band points are tracked, wherein a temperature profile for individual band points is determined and wherein, taking into account side conditions at least one target function for a plurality of actuators in a control range of the system, in particular in the cooling line is formed.

By taking into account secondary conditions, which preferably correspond to plant limits or control limits, it becomes possible, in particular for different cooling line layouts and, above all, in the case of a predetermined temperature or cooling curve, to determine (control) specifications, the control limits are more meaningful Consider the way. Thus, it is avoided, for example, in a two-part cooling section, that the specification of an excessively high temperature between the two partial cooling sections has the result that the reel temperature can no longer be achieved with the available coolant quantity of the second partial cooling section. In this way, and in particular also by the tracking of the band points, the accuracy of the control or regulation is significantly improved.

Advantageously, the objective function is minimized or maximized by solving an optimization problem. Such a control or regulation is also possible if a temperature or cooling is specified, which is not exactly feasible. The method then determines the best possible approximation.

Advantageously, a quadratic optimization problem is solved. Thus, the time to solve the optimization problem is usually significantly reduced.

Advantageously, the actual temperature profile and / or the desired temperature profile of the metal strip is determined with the aid of at least one model. In this way, improved control or regulation of the temperature of the metal strip is also made possible if the actual strip temperature at locations relevant for the control or regulation, in particular the cooling section, can not be measured.

Alternatively or additionally, the actual enthalpy profile and / or the desired enthalpy profile are determined.

Advantageously, the objective function is minimized or maximized by solving an optimization problem by means of precalculation. In particular, the time required for presetting the actuators is significantly reduced in this way. Preferably, in addition, the actuators are optimally preset with regard to a subsequent online control,

Advantageously, the objective function is preferably minimized or maximized online by solving an optimization problem.

Advantageous developments of the method are specified in claims 8 to 14.

Further solutions of the object according to the invention are specified in claims 15 to 18.

FIG 1

den prinzipiellen Aufbau eines Walzwerks,

FIG 2

die Kühlstrecke eines Walzwerks sowie eine zu deren Steuerung bzw. Regelung dienende Recheneinrichtung,

FIG 3

eine Kühlstrecke und eine ihr schematisch zugeordnete Kühlstreckenregelung,

FIG 4

mögliche Module einer Kühlstreckenregelung,

FIG 5

Vorausberechnung und eine Echtzeitregelung einer Kühlstrecke,

FIG 6

einen möglichen Temperaturverlauf eines Metallbandes in der Kühlstrecke.

Further advantages and details emerge from the following description of several embodiments of the invention in conjunction with the drawings. Here are an example:

FIG. 1

the basic structure of a rolling mill,

FIG. 2

the cooling section of a rolling mill as well as a computing device serving for its control or regulation,

FIG. 3

a cooling section and a cooling line control, which is assigned to it schematically,

FIG. 4

possible modules of a cooling line control,

FIG. 5

Precalculation and real-time control of a cooling line,

FIG. 6

a possible temperature profile of a metal strip in the cooling section.

FIG. 1 shows a plant for the production of metal strip 6, which comprises a roughing train 2, a finishing train 3 and a cooling line 4. The metal strip 6 is preferably rolled hot. Behind the cooling section 4, a reel device 5 is preferably arranged. From her rolled in the streets 2 and 3 and cooled in the cooling section 4 metal strip 6 is reeled. The streets 2 and 3, a band source 1 is arranged upstream. The band source 1 is designed, for example, as a furnace in which metal slabs are heated. The band source 1 may for example also be formed as a continuous casting plant, is produced in the metal strip 6, which is then fed to the roughing train 2.

The plant for steelmaking and in particular the roads 2, 3 and the cooling section 4 and the at least one reel device 5 are controlled by means of a control method which is carried out by a computing device 10. For this purpose, the computing device 10 is coupled with one or more of the components 1 to 5 of the plant for steel production control technology. The computing device 10 is programmed with a computer program designed as a control program, based on which it performs the inventive method for controlling or regulating the temperature of the metal strip 6.

According to FIG. 1, the metal strip or slab 6 leaves the strip source 1 and is first rolled in the roughing train 2 to an input thickness for the finished section 3. Within the finishing train, the belt 6 is then by means of the rolling stands 3 ' rolled to its final thickness. The subsequent cooling section 4 cools the belt to a predetermined reel temperature.

In order to ensure desired mechanical properties of the belt 6, a suitable temperature profile for the finishing train 3 and for the cooling section 4 must be complied with. For this purpose, a target temperature profile is preferably predetermined as a function of, for example, the type of installation, the operating mode, the respective application and desired properties of the metal strip 6.

FIG. 5 shows a computing device 10 for controlling a cooling section 4. In this case, the computing device 10 has a prediction module 21 and a module 22 for preferably online calculations, in particular during the cooling process.

By means of the prediction module 21, the actuators of the finishing train 4 can be initialized. For this purpose, for example, estimated values for missing measured values, for example the input speed of the metal strip, the temperature of the metal strip at the end of the finishing train 3 and the strip thickness, are used. By way of example, desired material values 105 serve as input-side input values for the prediction module 21.

The prediction 20 within the prediction module 21 is iteratively executed. This means that calculations with different amounts of coolant are repeated until predetermined errors are minimized. The pre-calculation 20 is therefore coupled with online-enabled cooling-distance monitor 11 and an A-adaptation 18.

The calculation module 22 has a cooling line monitor 11 and a cooling line control 12, which are coupled together. The cooling line monitor 11 and the cooling line control 12 control the actuators of the cooling section 4 and are preferably with one or more models of the cooling section, which may be stored, for example, in a model library 19. Preferably, one of the models is used to control the actuators. The cooling line control 12 sends control signals 101 to the cooling section 4, for example in the form of control patterns for coolant valves.

Figure 2 describes the operation of the cooling distance monitor 11 and the cooling line control 12 in more detail.

The cooling distance monitor 11 determines the state of the cooling section 4. The input parameters for the cooling section monitor 11 are, for example, values such as the speed of the metal strip 6, strip temperatures and coolant temperatures and coolant pressure.

Other inputs are the settings of the actuators, i. So preferably the valves. 7

Preferably, a final rolling temperature measuring station 8 for measuring the temperature of the metal strip 6 is arranged in the entrance area of the cooling section 4. Here the temperature of the end of the finishing train 3 or the temperature between the finishing train 3 and the cooling section 4 is measured. At the end of the cooling section 4, a final temperature measuring station 9 is preferably arranged. Here, the temperature is measured in front of the reel device 5 or at the end of the cooling section 4. Input variables of the cooling distance monitor 11 are the input temperatures 103 of the metal strip determined at the final rolling temperature measuring station 8, the starting temperatures 104 of the metal strip determined at the coiling temperature measuring station 9 as well as further band data 102 which are preferably located in the finishing train 3, e.g. at or shortly after the last rolling stand 3 ', are determined.

From the cooling line control 12 11 valve positions 101 are transmitted to the cooling line monitor, which, however, usually checked by the cooling line monitor 11 for plausibility become. The cooling distance monitor 11 always determines the current state of the cooling section 4.

The control or regulation according to the invention takes place clock cycle, preferably in control steps. The cooling line control 12 determines the valve positions 101 of the valves 7 of the cooling section 4 for the next control step. In this case, an optimization problem is preferably solved, which will be discussed in more detail in the text

According to the invention, an iteration step is preferably carried out in each time cycle, wherein, starting from the solution of the optimization problem assigned to a current time cycle, at least one actuating signal is applied to the installation. Preferably, further updated measured values are taken into account in the solution of the optimization problem for a subsequent clock cycle. In this way, a closed loop can be formed.

It is advantageous if at a high number of actuators, as is typical for the cooling section 4, not individual valves but groups of valves are considered as an actuator in the preparation of the preferably quadratic optimization problem. The distribution of the calculated control value to the individual valves is carried out via a suitable switching heuristic. The grouping of valves into valve groups is especially for an online, i. in real time, successful solution of the optimization problem particularly advantageous.

Figure 6 shows a possible temperature profile T over the locations x of the cooling section 4, wherein the cooling section 4 is limited by the beginning of the cooling section x _A and the end of the cooling section x _E. A comparable image would result from applying a temperature history T over time.

FIG. 3 illustrates the model-predictive control of the cooling section in more detail. In this case, preferably not individual valves 7a or 7b, referred to collectively as 7, are actuated by the cooling-zone controller 12, but rather valve groups consisting of one or more valves 7. In this case, for example, the control region 14 can be divided into a plurality of subregions 14a and 14b, wherein preferably each subregion 14a or 14b is assigned a valve group.

Within the limits of the control range 14, the boundaries of which usually coincide with the limits of the cooling path, a distinction can be made with regard to the control between a main control range 15 and a trim control range 16. Preferably, individual band points (13a, 13b) are tracked.

A model-predictive algorithm is used to control and regulate the cooling section. In this case, actuators for N _{u time} steps are determined in the future as a solution of a preferably quadratic optimization problem, wherein predictions are made with the model for N _{y time} steps.

N _u may be 1 or even a natural number greater than 1. In the latter case, only the calculated actuator settings for the first time step are usually implemented. For the next time step, we recalculated taking into account current measured values or predicted values.

N _y must be chosen large enough to overcome the largest dead time available. The largest dead time results from the largest distance of a temperature measuring point and the position of the nearest upstream free control valve. To set up the preferably quadratic optimization problem, a suitable, preferably linearized, strip temperature model is used. In the preferably square Optimization problem can easily be integrated with equation and inequality constraints. In this way, actuator limitations and different cooling line layouts can be taken into account particularly advantageously and preferably such that no excessive changes have to be made to the computing device 10 or to the prediction module 21 and / or the calculation module 22.

Alternatively or additionally, a model predictive control of the cooling section can also be based on the enthalpy curve in the cooling section. The enthalpy profile over the location x or over time is comparable to the temperature profile over the location (see also FIG. 6) or over time.

As FIG. 4 illustrates, it is possible for the computing device 10 to have a cooling line control module 12, which in turn has a plurality of partial control modules 17a, 17b, which correspond to different control regions 14a and 14b.

The control or regulation of the cooling section 4 according to the invention is independent of the cooling route layout and, because of the model-predictive control, also offers optimum control of the control limits at the control limits. Specifications can be weighted differently in terms of prioritization in a flexible way. Edge-masking can be integrated into the control method according to the invention.

The method according to the invention can be designed in such a way that the speed of the metal strip 6 can also be controlled, which makes its use possible, for example, also for heavy plate mills.

In particular, a finishing train 3 can also be regulated according to the invention. In addition to belt speed 3 interstand cooling devices are further possible actuators in a finishing line. A typical number of actuators for one Cooling section, for example, about 200 valves 7. This is a significantly higher number of actuators than for a typical finishing line. 3

An overall control for a plurality of plant parts 1 to 5 can preferably be achieved as described below, for example for a finishing train 3 and a cooling section 4.

For overall control or regulation, preferably the temperature model of the finishing train 3 and the temperature model of the cooling section 4 are concatenated. By adding the objective functions for both equipment parts 3 and 4, a preferably quadratic optimization problem with preferably linear secondary conditions is determined, by means of which a common control method is provided for both equipment parts 3 and 4. The optimization of the problem thus provides the settings for the interstitial cooling of the finishing train 3, the cooling line valves 7 of the cooling section 4 and speed of the metal strip 6, in particular for each next control step.

Claims (18)

1. Method for controlling and/or regulating the temperature of strip metal (5) in a system employed in the steel industry, especially in a cooling path (4) located downstream of a rolling train (2,3) for rolling a hot strip metal (6), wherein a desired temperature gradient is compared for the purpose of determining adjusting signals with an actual temperature gradient, characterised in that points (13a, 13b) on the strip are route-tracked, in that a temperature gradient is determined for individual points (13a, 13b) on the strip, and in that at least one target function is formed for a plurality of actuators in a regulating section of the system, especially in the cooling path (4), taking secondary conditions into account.
2. Method according to claim 1,
   characterised in that the target function is minimised by solving an optimisation problem.
3. Method according to claim 1 or 2,
   characterised in that the target function is maximised by solving an optimisation problem.
4. Method according to claim 2 or 3,
   characterised in that a quadratic optimisation problem is solved.
5. Method according to one of the preceding claims,
   characterised in that the actual temperature gradient and/or desired temperature gradient of the strip metal (6) is determined with the aid of at least one model.
6. Method according to one of the preceding claims,
   characterised in that the actual enthalpy gradient and/or desired enthalpy gradient is determined with the aid of at least one model.
7. Method according to claim 5 or 6,
   characterised in that the model is adapted online.
8. Method according to one of claims 2 to 7,
   characterised in that the target function is minimised or maximised by solving an optimisation problem using predictive calculating.
9. Method according to one of the preceding claims,
   characterised in that the target function is iteratively minimised or maximised preferably online by solving an optimisation problem.
10. Method according to claim 9,
    characterised in that an iteration step is carried out during each clocked pulse with at least one adjusting signal being applied to the system proceeding from the optimisation problem's solution assigned to a current clocked pulse.
11. Method according to claim 10,
    characterised in that further measurands are taken into account for a succeeding clocked pulse when the optimisation problem is being solved.
12. Method according to claim 11,
    characterised in that a closed control loop is formed.
13. Method according to one of the preceding claims,
    characterised in that the optimisation problem is solved with linear secondary conditions.
14. Method according to one of the preceding claims,
    characterised in that the temperature of the strip metal (5) is controlled and/or regulated in a plurality of parts (1 to 5) of the system employed in the steel industry, especially in the finishing train (3) and a cooling path (4) located downstream thereof.
15. Computer-program product comprising program-code means suitable for executing the steps of a method according to one of the preceding claims when the computer-program product is embodied on a calculating device.
16. Calculating device (10) for executing the method according to one of claims 1 to 14, wherein the calculating device (10) directly and/or indirectly influences the temperature of the strip metal (6), characterised in that the calculating device has been programmed by means of a computer-program product according to claim 15.
17. Calculating device (10) according to claim 16,
    characterised in that it has a cooling-path monitor (11), a module for predictive calculating (20), a module for adapting (18), and a module for cooling-path regulating (12).
18. Calculating device (10) according to claim 16 or 17,
    characterised in that it has a plurality of regulating modules (17a, 17b) for regulating actuators (7) and/or regulating regulating sections (14a, 14b) comprising one or more actuators.

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