Patent Application
20230203612
The invention relates to a method for controlling or regulating the temperature of a steel strip in hot forming in a hot strip mill.
Hot forming of a steel strip usually takes place in a hot strip mill. Said hot strip mill consists of different individual units such as, for example, furnaces, roll stands, drives, unwinding and winding systems for the steel strip, or cooling sections. A large number of different devices or methods are known for open-loop or closed-loop control of such units. These open-loop or closed-loop controls are essentially based on a target/actual value comparison and deriving appropriate corrective measures to maintain the target value. Here, the target values to be observed are defined on the basis of empirical knowledge and/or previous process analyses. Furthermore, a relationship between the product properties of the steel strip and the target values of the unit to be set is usually established in advance. In production of the steel strip, there is usually a complex relationship between a wide variety of target values and the desired product properties.
Due to the increasing digitization of plant technology, unit-related process models are used for the development of suitable target values that lead to the desired product properties. Depending on the data available, complexity of the relationships and/or effort, statistical models, analytical models or neural networks are used for these unit-related process models, for example.
The disadvantage of such closed-loop control concepts for hot strip mills having multiple units is that interactions when changing target value specifications or actual values across the various units are not mapped by the unit-related process models and/or open-loop or closed-loop controls of the units. Especially in the production of steel strips with high demands on the material quality, the complex interaction of time, temperature, structure development and by these quasi-static closed-loop controls of individual aggregates can be difficult to optimize.
Furthermore, open-loop or closed-loop controls of individual units of a hot strip mill are disadvantageous in that an optimization of the process control of the individual unit does not always necessarily lead to the optimization of the entire production process. In particular in combined systems with, for example, continuous casting systems, energy and production costs can be saved through more dynamic process controls.
It is the object of the invention to further develop known open-loop or closed-loop controls of a hot strip mill such that the target value specifications for the individual units are optimized across the plant with regard to the product properties of a steel strip, for example.
The object of the invention is achieved with a method. On a data processing system assigned to the hot strip mill, a superordinate process model exchanges and/or stores online target and/or actual values, including times, speeds, temperature, cooling rates and/or heating rates, with at least two open-loop or closed loop controls of the units. The superordinate process model, based on the exchanged target and/or actual values and/or stored values and using subordinate process models, such as, for example, a temperature model of the furnace, a temperature model of the cooling section or a model of the forming in the hot strip mill, predetermines the temperature of the steel strip online for at least one point before the hot strip is coiled. The superordinate process model determines new target value specifications for the units at this point in case of deviations in the predetermined temperature from a target value specification, transfers the target value specifications to the open-loop controller or closed-loop controller of the unit in order to comply with the target value specification for the temperature of the steel strip. The determination of the new target value specifications is carried out by using an optimization algorithm including at least one subordinate process model.
The superordinate process model maps a current production status of the steel strip based on the target and/or actual values of the units. Through suitable process models, such as, for example, energy and material balances for a homogenization furnace or a statistical model for that microstructural development of a steel strip, the superordinate process model determines the future development of a temperature profile before, for example, coiling. As a result, a difference between the target value specification for this individual unit and a possible deviation can be identified at an early stage. An optimization algorithm running in the superordinate optimization model can optimize target value specifications such that the target value specification for the hot strip before coiling is achieved, taking into account previously specified optimization goals. The optimization goals defined in advance can be, for example, production goals, in particular amounts of energy, production quantities or quality goals.
Preferred embodiments of the method are presented in the features of the disclosure. According to the disclosure, it is preferred that the preliminary product is a slab with a thickness dB ≥ 1 mm to dB ≤ 300 mm, preferably dB ≥ 50 mm to dB ≤ 160 mm from a casting machine and that the superordinate process model takes into account a casting speed, preferably between vG ≥ 4 m/min and vG ≤ 6 m/min, more preferably vG ≥ 5 m/min and vG ≤ 6 m/min, and a casting machine outlet temperature, preferably TGE ≥ 800° C. of the slab when determining the target specifications.
Preferably, according to the disclosure, the optimization target comprises energy consumption, production volume, process reliability, product properties, production costs and/or plant wear, the preferred reference variables in the field of steel production.
Furthermore, according to the disclosure, it is preferred if a subordinate process model determines the structure development of the steel strip in the hot strip mill for at least one point, preferably before the hot strip is coiled. In addition to the optimized temperature control, the resulting structure development is crucial for the further material properties and/or processing of the steel strip. The more precise open-loop or closed-loop control of the structure development in the course of the process makes it possible to react to deviations at an early stage and to reduce the quantities of rejects and/or post-treatments.
According to the disclosure, a roughing stand and a finishing stand are ideally used in hot forming. By dividing hot forming into a roughing stand and a finishing stand, advantageous temperature distributions and sequences can be set and these can also be better mapped by a larger number of measuring and control points. This enables the superordinate process model to react better to deviations. Furthermore, there are more opportunities to intervene in target value specifications of hot rolling.
It is preferred, according to the disclosure, that a temperature target value of TFS ≥ 850° C. to TFS ≤ 1050° C., preferably TFS ≥ 900° C. to TFS ≤ 1000° C., even more preferably TFS ≥ 900° C. to TFS ≤ 950° C. is specified by the superordinate process model for the target value of the inlet temperature into the finishing stand. Furthermore, it is preferred if a temperature target value within TFE ≥750° C. to TFE ≤ 950° C., preferably TFE ≥ 750° C. to TFE ≤ 900° C., more preferably TFE ≥ 800° C. to TFE ≤ 850° C. is specified by the superordinate process model for the target value of the outlet temperature out of the finishing stand.
According to the disclosure, a speed target value of vF ≥ 0.4 m/s to vF ≤ 1 m/s is specified by the superordinate process model for the target value of the inlet speed into the finishing stand.
According to the disclosure, a temperature target value of Tvs ≥ 1000° C. to Tvs ≤ 1150° C. is specified by the superordinate process model for the target value of the inlet temperature into the roughing stand. The target value of the outlet temperature from the roughing stand is specified by the superordinate process model for in a temperature range of TVE ≥ 950° C. to TVE ≤ 1100° C.
Ideally, according to the disclosure, a target value of dFS ≥ 20 mm to dFS ≤ 70 mm is specified by the superordinate process model for the target value of the inlet thickness into the finishing stand. The target value of the coiling temperature is preferably specified by the process model in the range from TH ≥ 30° C. to TVE ≤ 750° C., more preferably TH ≥ 450° C. to TH ≤ 550° C.
According to the disclosure, it is preferred if the alloying element C is limited to a content of 0.03% by weight to 0.15% by weight and/or Mn is limited to a content of 0.50% by weight to 2.00% by weight in the steel strip.
According to the disclosure, it is preferred if the optimized target value specifications are used for the production of a subsequent hot strip with the same production goals, in particular mechanical property. As a result, already existing optimized process sequences, which are described by the corresponding target value specifications, can be related to further production of the same material or steel strip type. This saves optimization time and makes it possible to react to gradual plant changes in advance.
Preferably, according to the disclosure, on a data processing system assigned to the hot strip mill, a superordinate process model can exchange and/or store online target and/or actual values, including times, speeds, temperature, cooling rates and/or heating rates, with at least two open-loop or closed-loop controllers of the units. The superordinate process model, based on the exchanged target and/or actual values and/or stored values and using subordinate process models, predetermines the temperature of the steel strip online for at least one point before the hot strip is coiled, and determines new target value specifications of the respective units at this point in case of deviations in the predetermined temperature from a target value specification. The new target value specifications are transferred to the open-loop or closed-loop controller of the respective unit in order to comply with the target value specification for the temperature of the steel strip. The determination of the new target value specifications is carried out by using an optimization algorithm including at least one subordinate process model.
The method according to the invention is described in detail below with reference to the figures mentioned in the form of exemplary embodiments. In all figures, the same technical elements are denoted by the same reference numerals.
The following three figures are attached to the description:
If the values within the unit are not reached, the subordinate process model III a, b can adjust the target specification. Likewise, an automatic optimization of the process model IIIa, b can also take place here by means of a self-learning algorithm. If the actual target value deviates from the target value specification V of the superordinate process model II, the target values are recalculated on the superordinate level II and adjusted if necessary.
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| Number | Date | Country | Kind |
|---|---|---|---|
| 10 2020 205 655.2 | May 2020 | DE | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2021/057720 | 3/25/2021 | WO |
