TW201609283A - Rolling simulation device - Google Patents

Abstract

The present invention has as its object the provision of a rolling simulation device capable of realizing high-accuracy rolling simulations. Provided is a rolling simulation device which is connected to a rolling system equipped with a rolling line and a setting computer. The rolling simulation device has a simulation condition setting part which sets simulation conditions concerning product quality and operation conditions in virtual operations which involve heating, rolling, cooling and conveying virtual metal materials in the rolling line. Also, the rolling simulation device has a virtual rolling line setting calculation part which calculates, with the aid of a first model formula and a similar second model formula which the setting computer has, control target values of an actuator group provided in the rolling line and state prediction values of the virtual metal materials so that the simulation conditions are achieved. Furthermore, the rolling simulation device has a parameter update part which updates a model parameter group of the second model formula on the basis of a model parameter group of the first model formula in the case where the model parameter group of the first model formula has been updated.

Description

Calendering simulator

The invention relates to a calendering simulation device, which simulates a rolling line and a rolling operation for manufacturing a metal product, and predicts the stability of the operation when the metal material is changed in size or alloy composition, heating, calendering, cooling target value and processing. Intermediate material, product quality.

In a metal material such as steel, materials such as mechanical properties (strength, formability, toughness, etc.) and electromagnetic properties (magnetic permeability, etc.) vary depending on the alloy composition, heating conditions, processing conditions, and cooling conditions. The alloy composition is adjusted by controlling the amount of the component element to be added, and when the component is adjusted, for example, a component adjustment furnace capable of holding a molten steel of about 100 tons is used, and one batch unit is large. Therefore, it is impossible to change the addition according to each product of about 15 tons. Therefore, in order to manufacture a product of a desired material, it is important to prepare a material by appropriately setting heating conditions, processing conditions, and cooling conditions. Furthermore, these processing conditions are important not only for the material but also for the quality of the product such as the size and shape of the product, and the realization of stable work.

In the hot rolling calendering process, the products are classified and produced by changing the target values of various processing parameters belonging to the processing conditions of the product quality or the working conditions. The processing parameters are, for example, the temperature at the inlet side of the finish rolling, The target temperature at each point on the rolling line represented by the finish rolling side temperature, the coiling temperature, etc., the plate thickness schedule of each channel, the use of each channel installed in the descaling of the calender, and the configuration The use of the internal pedestal cooler between the pedestals of the continuous rolling mill and the initial flow rate, the amount of lubricating oil used in the finishing rolling mill, and the cooling mode used in the delivery station.

In order to achieve the desired product quality, that is, in order to achieve the target values of the various processing parameters described above, the processing control by the setting computer is performed.

The computer system is configured to perform a setting calculation by using a model formula showing physical phenomena such as heating, rolling, cooling, and transportation, so as to achieve the target values of the various processing parameters described above. In the setting calculation, the calculation of the control target value of each actuator and the prediction calculation of the state of the rolled material (metal material) in each stage of the process are repeatedly performed.

The model formula for calculating the physical quantities such as the rolling load, the deformation resistance, the roll gap, the temperature, and the particle size used in the calculation calculation is expressed by a function of an input variable, a mechanical constant, an adjustment term, and a learning term.

Patent Document 1 or Patent Document 2 discloses a method in which a computer system sets an actual value such as a model prediction value and a temperature, a shape, a plate thickness, a plate width, and a rolling load obtained by a sensor provided on a rolling line. Compare and automatically learn the model-based learning items in advance so that the accuracy of the model and the method of controlling the accuracy of the model can be improved.

Further, in Patent Document 3, there is proposed a method of predicting a material for predicting a change in microstructure of a rolled material and a mechanical property of a final product, using a pull for a coil of a part of the product. The method of model learning is carried out by measuring the actual value of the mechanical properties obtained from the test results of mechanical properties such as tensile test or tissue observation. In general, the model parameters (mechanical constants, adjustment items, learning items) are based on factors that are easy to generate model errors, such as steel grade, target thickness, target panel width, target temperature, etc. Managed within the database.

Further, Applicants recognize the following documents including the above documents as a related to the present invention.

(previous technical literature) (Patent Literature)

(Patent Document 1) Japanese Patent No. 4119684

(Patent Document 2) Japanese Patent No. 4402502

(Patent Document 3) Japanese Patent Laid-Open Publication No. 2010-172962

(Patent Document 4) Japanese Patent Laid-Open Publication No. 2001-25805

(Non-patent literature)

(Non-Patent Document 1) Plastic Processing Technology Series 7 Plate Calendering ( Society) pp. 198-229

(Non-Patent Document 2) The 173th and 174th Nishiyama Memorial Technical Lectures "Predicting the Organizational Changes and Materials of Hot-Temperature Steel" (Journal of Japan Iron and Steel Association) Page 125

In the past, the processing parameters of the rolling operation were based on each system. The product specification has been determined over the years, and in order to achieve the above decision, it is generally a method of temperature control and size control. However, in recent years, the requirements for product specifications have become more highly diverse and diversified, and it is not always possible to appropriately determine such target values using empirical methods, and there is also a final quality that cannot achieve the desired size or mechanical properties. The situation. In addition, it may be difficult to determine whether it is possible to achieve the target value of the processing parameters with the existing equipment.

Therefore, in order to review in advance whether a product manufactured under an alloy composition and processing parameters can obtain the desired product quality, a processing model that utilizes various manufacturing steps for heating, processing, and cooling is proposed, and is offline. A device that simulates a manufacturing step (for example, Patent Document 4). The simulation device predicts the state of the metal material at each time, the temperature, the position on the manufacturing line, etc., and the information on the alloy composition of the metal material and the processing history record and temperature history record obtained from the simulation of the manufacturing step are used as input values. And by using the micro-organization prediction model to predict the change of the microstructure of the rolled material at each moment and the mechanical properties of the final product. In addition, the simulation device is also used to find the target values of the alloy composition and processing parameters for which the desired quality can be obtained.

In the simulation, the same model as the model used for the actual operation setting calculation, the simplified model, or a highly accurate model in which a part of the model is faithfully modeled into a physical phenomenon is used. The simulation system does not use the setting computer used for the actual work, and the database for managing the above-mentioned processing parameters or model parameters, but separately prepares a computer and a database dedicated to the simulation. Simulated and used while simulating the actual rolling operation The same is true for the same function as the model used for the actual job setting calculation. This is because the calculations used for simulation and the load generated by reading and writing the database cannot affect the actual operation.

The actual operation is performed for several rolled materials in the heating furnace according to the calculation calculation of the setting calculation, according to the setting calculation when the heating furnace is taken out, and after the extraction according to the actual value collected at any time during the rolling, repeatedly executing several times to several tens The second setting calculation. The parameters to be used, the actual values to be collected, and the output of the set calculations are due to the large amount of data and the frequent exchange of data, so the load on the database is greatly increased. Furthermore, the same setting calculation or writing to the database is performed for the plurality of rolled materials before and after the rolled material. Due to the rapid increase in the calculation load and the reading and writing of the high frequency of the database, when the calculation of the actual operation is calculated, the rolling operation has to be stopped and a large loss is caused. In the actual operation setting calculation, the timing of the calculation, the access method to the database, and the timing are closely designed according to the rolling pitch of the device and the number of collected data points.

However, in the case of simulation, since the simulated processing is calculated offline, unlike the processing control of the actual rolling operation, the load or temperature and size obtained by the sensors provided at the respective portions of the processing cannot be obtained. The actual value and the actual value of the mechanical properties of the product coil. Therefore, the actual pressure delay under the same conditions as the simulation, whether the target value of the processing parameter or even the target product quality is achieved, cannot be completely confirmed from the simulation. In addition, since various controls such as feedforward, feedback, and dynamics in the rolling according to the actual value are not implemented, when the model prediction error is generated, the model prediction error is accumulated, and the later stage is Processing, the difference between the target value and the actual value of the processing parameter is larger, and the product quality cannot be correctly predicted. Therefore, the accuracy of the model used for the simulation (especially the accuracy of the model parameters) is inherently related to the accuracy of the simulation, ie the extent to which the actual calendering operation can be simulated.

However, the manufacturing line and the metal material are simulated under the model of the simulation, and the calculation of the actual operation means that the adjustment item or the learning item in the model type is not shared by the computer or the database belonging to the computer. The mechanical constant indicating the mechanical properties of each actuator has not been updated. In Patent Document 4, in order to simulate a real rolling line in the case where device updating is performed, a strategy for easily correcting model parameters related to the device is performed. However, the types of parameters of the learning items and adjustment items of the model are large, and are frequently updated every time calendering or each adjustment, so it is difficult to appropriately correct the parameters at each change. At this time, unlike the model of the computer existing in the control or prediction of the actual operation, the actual calendering process cannot be accurately simulated, so even if the alloy composition and processing parameters used in the simulation are applied to the actual operation, There is a problem that the quality of the desired product cannot be obtained.

The present invention has been made in order to solve the above problems, and an object of the present invention is to provide a calendering simulation apparatus which can accurately simulate a virtual metal material using a rolling line of an actual operation on a computer different from a computer to be actually operated. The calendering process.

In order to achieve the above object, the first invention is a connection a rolling simulation device for a rolling system, comprising: a rolling line having an actuator group for heating, rolling, cooling, and transporting a metal material, and a control actual value for detecting the actuator group and the foregoing a sensor group of actual state values of the metal material; and a setting computer that calculates a control target value of the actuator group and/or a state prediction value of the metal material; and the setting computer system has a first model type, The first model type is a model expression showing physical phenomena of each process of heating, rolling, cooling, and transport in the rolling line, and is expressed by a function using input variables and model parameter groups as inputs, and the first The model formula calculates a control target value of the actuator group and a state predicted value of the metal material in a manner that achieves processing conditions related to product quality and/or operating conditions in an actual operation, and compares the control target value with The state predicted value, the comparison value between the control actual value detected by the sensor group and the actual value of the state, The model parameter group of the first model formula is updated at any time, and the rolling simulation device includes a simulation condition setting unit that sets a virtual operation for heating, rolling, cooling, and transporting the virtual metal material by the rolling line. The simulation condition relating to the product quality and/or the working condition; the virtual rolling line setting calculation unit has the second model equation similar to the first model formula described above, and the second model formula is used to achieve the simulation. a condition of calculating a control target value of the actuator group and a state prediction value of the virtual metal material; and a parameter update unit, based on the first model when the model parameter group of the first model expression is updated The aforementioned model parameter group of the formula is used to update the aforementioned model parameter group of the second model formula.

According to a second aspect of the invention, the parameter update unit includes: an update timing designating unit that specifies a timing at which calculation is not performed by the setting computer in an actual operation; and the parameter copying unit is in the sequence described above. The model parameter group of the first model formula is copied to the model parameter group of the second model formula.

According to a third aspect of the invention, the parameter update unit includes: an update parameter selection unit that selects the use of the virtual rolling line setting calculation unit in the model parameter group of the second model formula; The model of the simulation condition calculates a part of the model parameter group required; and the parameter copying unit is only for the model parameter group of the part selected by the update parameter selecting unit, and the model parameter group of the first model formula Make a copy.

According to the first aspect of the invention, when the model parameter group of the first model is updated, the model parameter group of the second model is updated based on the model parameter group of the first model. Thereby, the model parameters of the calendering simulation device can be updated to the latest information of the actual setting computer. Therefore, based on According to the first aspect of the invention, the rolling process of the virtual metal material using the actual working rolling line can be accurately simulated on a computer different from the actual setting computer.

According to the second or third aspect of the invention, it is possible to update the model parameters of the rolling simulation device to the latest data in the setting computer of the actual operation while suppressing an increase in the load imposed on the calculation in the setting computer of the actual operation.

1‧‧‧calendering line

10‧‧‧Transportation station

11‧‧‧heating furnace

12‧‧‧crude rolling machine

13‧‧‧Film with heater

14‧‧‧ Finishing calender entrance side thermometer

15‧‧‧Rolling calender

16‧‧‧Exhaust side thermometer for finishing rolling calender

17‧‧‧Send

18‧‧‧Winner inlet side thermometer

19‧‧‧Winding machine

20‧‧‧Depression system

21‧‧‧Control controller

23‧‧‧Set computer

24‧‧‧Depression simulator

25‧‧‧Upper computer

31‧‧‧ Simulation Condition Setting Department

32‧‧‧False rolling line setting calculation section

33‧‧‧Parameter Update Department

41‧‧‧Update Timing Designation Department

42‧‧‧Update parameter selection department

43‧‧‧Parameter Copy Department

Fig. 1 is a view showing an example of a rolled sheet of a hot rolled sheet according to Embodiment 1 of the present invention.

Fig. 2 is a block diagram showing a rolling system according to a first embodiment of the present invention.

Fig. 3 is a block diagram showing the function of the rolling simulation device 24 according to the first embodiment of the present invention.

Figure 4 is an input screen for inputting the chemical composition of a virtual metal material.

Fig. 5 is a view showing an example of a flat embryo heating mode in the heating furnace 11.

Fig. 6 is a view for explaining the cooling mode at the delivery station 17.

Fig. 7 is a view for explaining the cooling mode at the delivery station 17.

Fig. 8 is a view showing a model group and a model parameter table group which the virtual rolling line setting calculation unit 32 has.

The ninth figure is a figure explaining the process performed by the parameter update part 33.

Fig. 10 is a block diagram showing the configuration of the parameter updating unit 33.

Figure 11 shows the model parameters used in the calendering simulation device 24. A map of the updated timing that is suitable for the latest state of the new.

Fig. 12 is a view showing a specific example of a process of updating the adjustment items and the learning items required for the simulation to the latest state when the simulation execution command is accepted.

Fig. 13 is a flowchart showing a processing procedure for updating the parameters of the respective models existing in the virtual rolling line setting calculation unit 32 to the same values as the latest parameters used in the actual work.

Fig. 14 is a flow chart showing a procedure for reviewing the alloy composition and manufacturing conditions by the rolling simulation device 24.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In addition, the same elements in the respective drawings are denoted by the same reference numerals and the description thereof will not be repeated.

Embodiment 1 [System configuration of the first embodiment]

(rolling line)

Fig. 1 is a view showing an example of a rolled sheet of a hot rolled sheet according to Embodiment 1 of the present invention. The object to be described later is a simulator for simulating the hot rolled sheet rolling line shown in Fig. 1. In addition, this simulator can also be applied to other rolling lines.

The rolling line includes a heating device, a rolling machine, a cooling device, a winding device, and a transfer table that connects the devices. These devices are driven by actuators such as electric motors or hydraulic devices. Specifically, the rolling line 1 shown in Fig. 1 has the heating furnace 11, the rough calender 12, the strip heater 13, and the inlet side temperature of the finish rolling calender from the upstream side of the transfer table 10 in this order. The finisher 14, the finish rolling calender 15, the finish rolling calender outlet side thermometer 16, the run out table 17, the coiler inlet side thermometer 18, and the coiler 19.

The heating furnace 11 is a furnace for heating a slap. The heating furnace 11 is controlled to obtain a desired radish heating mode and a furnace extraction temperature. The rough calender 12 is composed of a single number or a plurality of pedestals, and in the example shown in Fig. 1, a reversible rough calender composed of one pedestal. The sheet heater 13 is a device for heating the rolled product by electromagnetic induction heating or the like in order to control the temperature of the rolled product (including the state from the flat embryo to the state in which the product is completed, and the same applies hereinafter). The finish rolling calender 15 is composed of a single number or a plurality of pedestals. In the example shown in Fig. 1, it is a tandem type finish rolling calender composed of seven pedestals. The delivery station 17 is a cooling device that cools the rolled product by cooling water in order to control the temperature of the rolled product. Further, the rolling line 1 may be provided with a cooling stage as a cooling device, a forced cooling device, or the like. The winder 19 is a device for winding up a rolled product and forming a shape that is easy to convey. The transfer table 10 transports the rolled product in each step to the apparatus of the next step. These devices are driven by actuators such as electric motors or hydraulic devices.

Fig. 2 is a block diagram showing a rolling system according to a first embodiment of the present invention. The rolling system 20 shown in Fig. 2 has a hierarchical structure of a hierarchy 0 to a hierarchy 3. The hierarchy 0 is composed of a drive control device that controls the motors for driving the devices of the rolling line 1, and a hydraulic device for driving the devices of the rolling line 1. The hierarchy 1 is composed of the control controller 21. The hierarchy 2 is composed of a setting computer 23. In addition, it can also be adopted The configuration of the controller is replaced by the setting computer 23. The hierarchy 3 is composed of a production management upper computer 25. The rolling simulation device 24 does not affect the rolling of the actual work, but is connected to the setting computer 23 in order to update the parameters.

(setting the computer)

In the hot rolling calendering process of the actual work, the products are classified and produced by changing the processing conditions relating to the product quality or the working conditions, that is, the target values of the various processing parameters described above. In order to achieve the desired product quality, that is, the processing control by the setting computer 23 is performed so as to achieve the target values of the various processing parameters described above.

The target value of the processing parameters is sometimes specified by the level 3 upper computer 25 located in the upper level of the setting computer 23 of the level 2. Further, the target value of the processing parameter is sometimes specified in the database to which the setting computer 23 belongs, and is specified by a steel type, a plate thickness, a board width, or the like. In addition, the target value of the processing parameters is sometimes changed by calendering by the operator.

The setting computer 23 has a model of a physical phenomenon in which each process such as heating, rolling, cooling, and conveyance of the rolling line 1 is displayed (hereinafter, the model type of the setting computer 23 is also referred to as "first model type"). . The setting computer 23 performs the setting calculation so as to achieve the target value (processing condition) of the various processing parameters in the actual operation by the first model formula. In the setting calculation, the calculation of the control target value of each actuator and the calculation of the state of the rolled material (predicted state of the metal material) in each stage of the process are repeatedly performed.

The control target value of the actuator refers to the roll gap of the calender, the rolling speed, the conveying speed, the flow of the chip removing or various sprayers, and the ON/OFF of the valve of the delivery table. The state of the rolled material in each stage of the treatment (predicted state of the state of the metal material) means size or shape, temperature, microstructure, and the like.

The control controller 21 controls various actuators so as to receive the setting calculation result from the setting computer 23 and follow the control target value. In the actual hot rolling calendering process, various sensors are provided around the rolling line to monitor and collect the actual values of the parameters affecting the process control such as temperature, shape, plate thickness, plate width, and rolling load.

These actual values are applied to the process control or model (first model) accuracy improvement and quality management. When the target value of the processing parameter, the actual value obtained by the various sensors, and the actual calculated value calculated from the actual value and the calculated value are compared, if the target value of the processing parameter is not reached, the setting calculation is performed again. According to the result, various controls such as feedforward control, feedback control, and dynamic control are performed.

The model formula (first model formula) for calculating the physical quantities such as the rolling load, the deformation resistance, the roll gap, the temperature, and the particle diameter used in the calculation calculation is based on the input variable and the model parameter group (mechanical constant, adjustment term, learning item). It is represented as a function of input. The input variable is the physical quantity associated with the model output. For example, when the model output is a rolling load, the deformation resistance, the width of the rolled material, the amount of reduction, and the like become input variables. The mechanical constant is a physical quantity indicating the mechanical properties of the actuator such as the roll diameter, the mill curve, the sprinkler flow rate, and the like of the calender roll. The mechanical constants are subject to change due to roll replacement, equipment repair or adjustment, and annual changes. Tune The entire item or learning item is used to improve the predictive accuracy of the model.

Even if the model of the treatment actively simulates the physical phenomenon, the model prediction error will also occur in reality. Therefore, the engineer fine-tunes the coefficients or constants of the various models in the model to improve the prediction accuracy of the model. Adjust the coefficient or constant of each item in the model, and use the factor that is easy to generate the model error, such as the steel type, the target thickness, the target plate width, the target temperature, etc., according to the layer table that is distinguished by the setting computer 23 Managed within the database. In addition to the start of the operation, the adjustments are mainly adjusted for the pressure delay of the new steel grade and the combination of new processing parameters. Adjustment items are sometimes adjusted by engineers based on experience or numerical analysis results. In recent years, statistical methods such as neural networks have been used to perform semi-automatic adjustments. The learning item is used to multiply and add the model formula in order to compensate for the model output and the error in the actual processing output.

(calendering simulation device)

Fig. 3 is a block diagram showing the function of the rolling simulation device 24 according to the first embodiment of the present invention. The calendering simulation device 24 simulates each treatment of the hot-rolled sheet rolling line shown in Fig. 1, and predicts the operation stability and treatment when changing the size or alloy composition of the metal material, the target value of heating, calendering, cooling, and the treatment. The state of the rolled material and the quality of the product on the way. The rolling simulation device 24 includes an simulation condition setting unit 31, a virtual rolling line setting calculation unit 32, and a parameter update unit 33. Further, the rolling simulation device 24 is provided with a computer for calculating the processing device, the memory device, and the input/output device. The memory device memorizes the processing of the processing contents of the above respective units. Each of the above units is processed by the execution of the memory device by the arithmetic processing device.

((simulation condition setting unit))

The simulation condition setting unit 31 sets simulation conditions relating to the product quality and the working conditions in the virtual operation of heating, rolling, cooling, and transporting the virtual metal material by the rolling line 1. Hereinafter, it demonstrates in detail.

The simulation condition setting unit 31 sets the parameter of the rolling operation process as the simulation condition in the rolling simulation device 24. Here, the parameters of the calendering process are, for example, the alloy composition and size of the rolled material given by the upper computer 25 in actual operation, the target plate thickness, the target plate width, the flat embryo heating mode in the heating furnace, and the furnace outlet. Side temperature, finish rolling outlet target temperature, finish rolling inlet target temperature, cooling mode, coiling target temperature, etc. Further, the parameters of the rolling operation process are, for example, predetermined in the actual operation for each steel type and each target thickness, and are set in advance by the setting computer 23, or by the amount and pressure of each channel given by the operator from the HMI. Lower rate allocation, board speed or acceleration rate.

Each of the simulation conditions is a work condition in which the metal material which is rolled in the actual operation stored in the actual work upper computer 25 or the setting computer 23 or the like, or the predetermined rolling is used, by the communication LAN or the memory medium. In addition to this, you can use hand input to set all or part of the conditions. In addition, the simulation conditions used in the past rolling simulation device may be reused, or a part of the simulation may be used.

Fig. 4 is an input screen for inputting the chemical composition of a virtual metal product (hypothetical metal material). In the actual work, since one batch unit is large and is about 15 tons, the amount of the alloy component cannot be changed depending on each product. Therefore, in the simulation condition setting unit 31, in order to be easy The change in the quality of the product at the time of changing the alloy composition is calculated by inputting the content (wt%) of each chemical component in each of the virtual metal products as shown in Fig. 4 . The alloy composition of the metal product calendered in the actual work or the alloy composition used in the past simulation can also be called as a reference value, and a part thereof is changed for simulation.

Fig. 5 is a view showing an example of a flat embryo heating mode in the heating furnace 11. The flat embryo heating mode or the furnace extraction temperature in the heating furnace 11 also affects the material quality and quality of the product. For example, when the flat embryo is not sufficiently heated, the solid solution amount of the micro alloy cannot be sufficiently obtained, and the solute drag effect by the solid solution microalloy is reduced, and after the extraction The amount of precipitation during rolling and cooling is reduced, and the pinning effect by the precipitate is reduced. Further, since the rolling of the low-temperature rolled material is performed by rolling the hard material, the rolling operation due to the increase in the rolling load of the calender is unstable, and the electric power consumption of the electric motor for rolling is increased. . The simulation condition setting unit 31 sets the flat embryo heating mode in the heating furnace 11 as shown in Fig. 5 . In the case where the temperature mode does not affect the quality or when simple calculation is to be performed, only the target value of the extraction temperature of the furnace is set.

In the actual operation, in order to manage the temperature of the rolled material in the rolling, the operator gives the target of the processing parameters such as the target temperature of the finishing rolling outlet, the target temperature of the finishing rolling inlet, and the target temperature of the coiling through the upper computer 25 or the HMI. The value is controlled such that the rolling speed, the heating mode of the heating device in the middle of the rolling line, and the cooling mode in the various sprinklers and delivery tables 17 are controlled so as to follow the target value. Regarding the cooling mode, there are also The situation specified by the bit computer 25. In the simulation condition setting unit 31, in order to confirm the influence of the product quality and the rolling operation when the temperature history in the rolling is changed by the simulation, the finishing rolling side target temperature, the finish rolling inlet target temperature, and the volume are set. The target temperature and the cooling mode at the delivery station 17 were taken as simulation conditions. Fig. 6 and Fig. 7 are views for explaining a setting example of the cooling mode of the delivery table 17. The cooling mode of the delivery station 17 is selected to preferentially use the front stage cooling of the upstream side cooling shown in Fig. 6, the cooling of the downstream side of the downstream side cooling equipment preferentially, and the slow mode of cooling using all the cooling devices. Further, there is a method of setting the cooling rate of the region where the water is cooled and the time for cooling the air to the target value. Further, in the cooling mode of the delivery table 17, the water cooling cooling is performed on the upstream side and the downstream side of the cooling device shown in Fig. 7, and the air cooling is performed in the middle, and for example, the water cooling rate on the upstream side is selected. The air cooling time and the method of setting the target temperature to the temperature at the intermediate point of the delivery station.

In the setting computer 23 used in the actual operation, in order to perform stable rolling and passing, the target values of the processing parameters such as the reduction amount or the reduction ratio of each channel, the plate speed or the acceleration rate are determined. The steel grade and each target thickness are distinguished in advance in the database. Alternatively, the operator inputs the target value of the processing parameter. On the other hand, in the rolling simulation device 24 used in the virtual work, the simulation condition setting unit 31 can simply calculate the reduction of the reduction amount or the reduction ratio of each channel, the plate speed or the acceleration rate, and the like. The simulation conditions are set in a way that affects the quality of the product or the operation of the rolling operation.

((imaginary rolling line setting calculation unit))

The virtual rolling line setting calculation unit 32 has the same model formula as the first model formula (referred to as a second model formula), and uses the second model formula to calculate the control target value or hypothesis of the actuator group so as to achieve the simulation condition. The predicted value of the state of the metal material. Hereinafter, it demonstrates in detail.

The virtual rolling line setting calculation unit 32 calculates the set value of each process for rolling the virtual metal material by the virtual rolling line, and the metal material at various times, so as to follow the respective target values given by the simulation condition setting unit 31. Size, location, temperature.

Fig. 8 is a view showing a model group and a model parameter table group which the virtual rolling line setting calculation unit 32 has. The virtual rolling line setting calculation unit 32 has a processing model, a transport model, a temperature model, and a material model as a model group. The processing model calculates the set values of the respective calendering processes of the heating device, the rolling device, the cooling device, and the like. The transfer model calculates the position of the imaginary metal material at each moment. The temperature model calculates the temperature of the imaginary metal material at each moment in each location. The material model predicts the microstructure of the metal material and the final product material at each moment of each place on the imaginary rolling line based on the alloy composition, processing history, and temperature. Further, the virtual rolling line setting calculation unit 32 has a memory device such as a data bank of the memory model parameter table group, and performs a joint calculation for each model formula for storing the parameters of the respective models described above.

The processing model calculates the following simulation condition setting unit 31 by using the position of the virtual metal material at each time point of each place given by the transfer model and the temperature of the virtual metal material at each time point of each place given by the temperature model. The set temperature of the furnace 11 given the target value Degree mode, calendar channel schedule, roll gap, processing history of imaginary metal materials at various times, size and shape, rolling speed, ON/Off setting and flow setting of various sprinklers, and cooling setting of the delivery station 17 .

The transport model calculates the position of the virtual metal material at each moment of each place by using the distance between the processes or the channel schedule given by the processing model. Further, the transport model calculates the transport speed following each target temperature using the temperature information of the virtual metal material given by the temperature model.

The temperature model is obtained from the size information of the virtual metal material in each process, the information of the mechanical factor, the channel schedule table given by the simulation condition setting unit 31 or the processing model, the roll gap, the rolling speed, the conveying speed, and the rolling line. The information of the command value such as the heating mode of the heating device is used to calculate the temperature of the virtual metal material at each time point in each place on the virtual rolling line.

The material model predicts the microstructure of the imaginary metal material during and after the rolling process by using the processing history record of the imaginary metal given by the processing model and the temperature history record given by the temperature model. The predicted microstructures are, for example, the fractions of various tissues such as particle size, dislocation density, Worthite iron, ferrite iron, and perlite. And, based on the microstructural prediction result, parameters related to mechanical properties such as stress or tensile strength are calculated. In the micro-organization prediction model that digitizes the metallurgical phenomenon, there are various proposals, and it is known that there are a number of groups representing static recovery, static recrystallization, dynamic recovery, dynamic recrystallization, grain growth, and the like. Constitute. One example is unveiled in the plastic processing technology series 7 plate calendering (CORONA) Pp. 198-229. It is well known that metal structure information and alloy composition can predict mechanical properties such as stress or tensile strength. An example of this is the 125th page of the 173th and 174th West Mountain Memorial Technical Lectures, "Predicting the Organizational Changes and Materials of Hot Steel" (published by the Japan Iron and Steel Association).

The above-described processing model, transport model, temperature model, and material model are expressed by the same function as the model formula (first model formula) of the setting computer 23 used in the actual work of hot rolling calendering. For example, in recent years, the architecture of all computers has been replicated by a virtual machine, and the methods imaginarily implemented on different computers have been widely adopted. Thereby, the model type (first model type) of the setting computer 23 used in the actual work and the database structure for managing the model parameters can be transferred to the rolling simulation device 24. Therefore, the rolling simulation device 24 has the same model formula (second model formula) as the first model. The model is expressed as the following equation by taking variables, mechanical constants, and adjustment terms as inputs.

Y = f ( X ₁ , X ₂ ,..., m ₁ , m ₂ ,..., a ₁ , a ₂ ) (1)

among them,

f: model without learning items

Y: model output without learning items

X _i : input variable associated with model f

m _i : mechanical constant

a _j : adjustment

The input variable is the physical quantity associated with the model output. For example, when the model output is a rolling load, the deformation resistance, the width of the rolled material, and the amount of reduction are equivalent to the input variables. The mechanical constant is a physical quantity indicating mechanical properties such as a roll diameter, a rolling curve, and a flow rate of a roll of a calender roll. The mechanical constant varies depending on roll replacement, periodic repair, equipment renewal, and annual changes. In the actual operation, the mechanical constant is managed by the table of the database to which the setting computer 23 belongs for the actual work, and is corrected at any time as the above changes. Adjustments are used to improve the predictive accuracy of the model. The adjustment item is set to reduce the model error and is a coefficient or constant that allows correction. The adjustment item is a layer table which is easy to generate a model error, for example, a steel sheet, a target thickness, a target board width, a target temperature, etc., and manages a database to which the setting computer 23 used in actual work belongs according to each layer. Inside. The adjustment item is adjusted in the actual operation, except for the start of the operation, mainly in the new steel type pressure delay, or the combination of new processing parameters. There are also cases where engineers adjust to the results of numerical analysis based on experience or actual operations. In recent years, statistical methods such as neural networks have been used to perform semi-automatic adjustments.

In the actual hot rolling and rolling process, various sensors are provided everywhere in the rolling line 1 to monitor and collect the actual values of the parameters affecting the process control such as temperature, shape, plate thickness, plate width, and rolling load. . These actual values are used for processing control or model (first model) accuracy improvement and quality management. The model predicts the calculated value, the actual value obtained by various sensors, and the actual calculated value calculated from the actual value and the calculated value, and makes the model learning to improve the usage model. The accuracy of the type and the method of using the model to control the accuracy. The learning term is used to multiply or add to the model formula in order to compensate for the output of the mode and the error of the output of the actual processing. The multiplication type and the addition type are respectively expressed in the following manner.

Multiplication type:

Y _L =Z _p . Y (2)

Addition type:

Y _L =Y+Z _A (3)

among them,

Y _L : model-based predictions of the learning

Y: model output without learning items

Z _p : multiplication type learning item

Z _A : Additional learning items

The learning item is updated with the actual value of the parameter that the sensor or the like obtains the output of the model. For example, in the multiplication type, the learning item is updated as follows.

among them,

Z _P ^ACT : Multiplication type learning item calculated based on actual value

Y ^ACT : actual value of the parameter according to the model output

Y: model output without learning items

Z _P ^NEW : updated multiplication type learning item

Z _P ^OLD : Multiplication learning item before update

A: Smoothing gain

The learning item is automatically updated by layer based on a layer table that is easily distinguished by a factor of model error, such as steel grade, target thickness, target panel width, target temperature, and the like. A material prediction model for predicting the microstructure of a rolled material and the mechanical properties of the final product, and the actual mechanical properties obtained by measuring the mechanical properties such as tensile test and tissue observation of a part of the product coil Value learning model. The model parameters (the first model formula) used for the calculation of the actual work calculation, that is, the mechanical constants, adjustment items, and learning items are managed in the database to which the actual work setting computer 23 belongs.

The model (second model) of the processing model, the transport model, the temperature model, and the material model included in the virtual rolling line setting calculation unit 32 of the rolling simulation device 24 of Fig. 8 is used and actually exists in the hot rolling calendering A function defined by the model (first model formula) of the setting computer 23 used for the job. Further, each of the parameters of the mechanical constant, the adjustment term, and the learning term is managed by the database to which the virtual rolling line setting calculation unit 32 belongs according to the model parameter table group stored in the layer. The table of the database to which the virtual rolling line setting calculation unit 32 belongs has the same structure as the table of the stored mechanical constants, adjustment items, and learning items in the database to which the setting computer 23 for actual work belongs.

((Parameter Update Department))

The ninth figure is a figure explaining the process performed by the parameter update part 33. When the model parameter group of the first model formula is updated, the parameter update unit 33 updates the model parameter group of the second model formula based on the model parameter group of the first model formula. Hereinafter, it demonstrates in detail.

In the parameter updating unit 33, as shown in FIG. 9, the model parameter of the model calculation unit 32 is set in accordance with the virtual rolling line, that is, the setting of the computer 23 in accordance with the mechanical constant, the adjustment item, and the learning item stored in the actual operation. The parameters of the parameter table group of the database are updated. In the simulation, unlike the actual control of the rolling operation, the actual value of the load or temperature, the actual value of the size, or the mechanical properties of the product coil obtained by the sensors disposed throughout the process cannot be obtained. The calculations resulting from the simulation and the load due to the reading and writing of the database must not affect the calculation of the actual operation. Therefore, in the simulation, the setting computer 23 and its database used in the actual operation are not used, but a computer and a database dedicated to simulation are used. Therefore, the mechanical constant, the adjustment term, and the learning term in the second model are not updated at the same timing as the first model of the setting computer 23 used for the actual work. The parameter update unit 33 updates the model parameters of the second model equation of the simulated virtual rolling line setting calculation unit 32, that is, the mechanical constants, the adjustment items, and the learning items, and does not affect the setting calculation of the actual work, and ensures that The actual job settings calculate the same mode accuracy.

Fig. 10 is a block diagram showing the configuration of the parameter updating unit 33. As shown in FIG. 10, the parameter update unit 33 includes an update timing designation unit 41, an update parameter selection unit 42, and a parameter copying unit 43. Update timing The fixed portion 41 automatically specifies the timing for updating the parameters of the simulator. For example, the timing at which the calculation is not performed by the setting computer 23 in the actual job is specified. The update parameter selection unit 42 selects a parameter to be updated. For example, a model parameter group of a part of the required calculation of the simulation condition of the virtual rolling line setting calculation unit 32 in the model parameter group of the second model is selected. The parameter copying unit 43 is based on the update timing obtained by the update timing designating unit 41, and only the model parameter group selected by the update parameter selecting unit 42 is stored from the first model of the database to which the setting computer 23 of the actual job belongs. The model parameter group is copied.

However, in the calculation of the actual operation, in the rolling operation, the calculation calculation of the setting calculation is performed for one rolled material in the heating furnace, and the setting calculation for the setting of the actuator is performed when the heating furnace is taken out. After the extraction, the actual value is collected, and based on the value, the setting calculation is performed several times to several tens of times. Since the parameters to be used, the actual values to be collected, and the output of the set calculations are also large and frequent, the load on the database is relatively large. Furthermore, since the same setting calculation and reading and writing of the data are performed on the plurality of rolled materials before and after the rolled material, the calculation timing is closely designed and managed according to the rolling pitch of the device, the number of collected data points, and the like. Access method and timing for the database.

However, during the period in which the rolling line is stopped, for example, during the period in which the line is stopped for ten minutes at a frequency of several hours, or during the period of periodic repairs in which the line is stopped for several hours to several tens of hours at a frequency of several days or even several weeks. The calculation load of the computer 23 or the reading and writing of the database will disappear, or the frequency of load or reading and writing will be significantly reduced. If it exists in a calendering die The update timing designation unit 41 of the parameter update unit 33 of the pseudo device 24 selects the update timing of the model parameters as the calender simulation device 24 during the above-described roll replacement, periodic repair, and device update of the actual work, and does not actually apply The setting calculation of the job has an impact.

The model parameters (mechanical constants, adjustment items, and learning items) used in the actual job setting calculation are updated at different timings. For example, the initial roll diameter of the calender rolls in the mechanical constant is changed by the replacement of the rolls every few hours. Even with the mechanical constant, the rolling curve as the tensile index of the calender is updated over a long-term interval of several months or even years. Although the flow rate of various sprinklers changes year by year, the amount of change is gentle, and it is difficult to measure the flow rate when the flow meter is not set in advance. Therefore, the flow rate of various sprinklers is such that when a defect occurs or when the device is updated, the measurement is not performed unless it is for special reasons. In addition to the start of the operation, the adjustments are mainly adjusted for the pressure delay of the new steel grade and the combination of new processing parameters. The learning item is the most frequently updated in these items. The learning item is managed according to a layered table that is easily distinguished by a factor of model error, such as steel grade, target thickness, target panel width, target temperature, etc., and is equivalent to the model layer associated with the calendering. The learning items will be updated. If the model parameters used by the calendering simulation device 24 are updated at the same frequency as the update frequency of the model parameters used in the actual work, the actual work can be accurately simulated.

Fig. 11 is a view showing an update timing suitable for updating the model parameters used by the rolling simulation device 24 to the latest state. For example, at the timing shown in Fig. 11, the parameters used in the calendering simulation device 24, Copy the same value as the actual job parameters. In the actual operation, the adjustment items and the learning items may be updated at a higher frequency than the regular repair and roll replacement, or at different timings. However, due to the large number of such parameters, the automatic updating of all parameters should be performed at the timing of the calender stop of the actual operation. On the other hand, in the rolling simulation device 24, the rolling operation is performed by the size or alloy composition of the rolled material to be simulated by the simulation condition setting unit 31, the target product size or material, the reduction ratio distribution, or the cooling mode. The simulation conditions such as the parameters are used to know the model parameters required for the simulation to be performed. Therefore, if the adjustment items and the learning items required for the simulation are updated to the latest state during the simulation execution, the rolling of the actual work can be accurately simulated under the conditions.

Fig. 12 is a view showing a specific example of a process of updating the adjustment items and the learning items required for the simulation to the latest state when the simulation execution command is accepted. First, the steel composition and thickness of the imaginary rolled material used for the simulation are identified by the composition of the alloy in the simulation conditions, the target thickness, and the like. In the example shown in Fig. 12, the simulation condition setting unit 31 sets the steel type = C, 0.1 ≦ plate thickness < 0.3 as a simulation condition.

The table group of the database to which the actual job setting computer 23 belongs and the table group of the database to which the calendaring simulation device 24 belongs have the same table structure, and data can be copied between the databases. The database is a table group with a set of adjustment items, a table of learning items, and a mechanical constant. In the example shown in Fig. 12, the update parameter selection unit 42 selects a parameter of steel type = C and 0.1 ≦ plate thickness < 0.3 as the update parameter from both of the table groups. The update parameter is notified to the update timing designation unit 41 and the parameter copying unit 43. Update timing The fixed part 41 confirms that the update of the selected parameter does not affect the setting calculation of the actual work. When there is no influence, the update timing is specified and notified to the parameter copying section 43. Then, the parameter copying unit 43 copies the selected update parameter from the database to which the actual job setting computer 23 belongs to the database to which the rolling simulation device 24 belongs, at the designated update timing.

(flow chart)

Fig. 13 is a flowchart showing the processing of updating the parameters of the respective models existing in the virtual rolling line setting calculation unit 32 to the same values as the latest parameters used in the actual work. This processing is repeatedly executed by the parameter updating unit 33.

In step S131, the parameter update unit 33 determines whether or not the rolling line 1 is in periodic repair. Specifically, the update timing designation unit 41 inquires of the control controller 21 or the setting computer 23 whether or not the rolling line 1 is in periodic repair. The update timing designation unit 41 determines whether or not the rolling line 1 is in periodic repair based on the result of the inquiry. In the case of regular repair, the processing of step S132 is performed. In the case of non-periodic repair, the processing of step S133 is performed.

In step S132, the parameter update unit 33 selects all of the model parameters as update parameters. In the case of regular repair, it is preferable to update all the parameters existing in the virtual rolling line setting calculation unit 32 to the same values as the latest parameters used by the actual work setting computer 23. Therefore, the update parameter selection unit 42 selects the full parameter at the time of regular repair.

In step S133, the parameter update unit 33 determines whether or not Perform roll replacement. Specifically, the update timing designation unit 41 inquires of the control controller 21 or the setting computer 23 whether or not the operation mode of the rolling line 1 is the roller replacement mode. The update timing designation unit 41 determines whether or not the roll replacement mode is based on the result of the query. In the case of the roll replacement mode, the process of step S134 is performed. In the case of the non-roller replacement mode, the process of step S135 is performed.

In step S134, the parameter updating unit 33 selects the mechanical constant associated with the roller and all the learning items as the update parameters. Specifically, the update parameter selection unit 42 selects the mechanical constant associated with the roller and all the learning items as the model parameters to be updated.

In step S135, the parameter update unit 33 determines whether or not the simulation execution instruction is to be performed. Specifically, the update timing instruction unit 41 of the parameter update unit 33 inquires of the simulation condition setting unit 31 whether or not the simulation condition is input and performs the simulation execution instruction. The parameter update unit 33 determines whether or not to execute the simulation execution command based on the result of the query. When the simulation execution instruction is performed, the processing of step S136 is performed.

In step S136, the parameter update unit 33 selects the learning item and the adjustment item related to the simulation condition as the update parameter before the execution of the simulation calculation. Specifically, the update parameter selection unit 42 selects the learning item and the adjustment item related to the simulation condition as the model parameter to be updated.

In step S137, the update timing designation unit 41 of the parameter update unit 33 determines whether or not the update of the parameter selected by the update parameter selection unit 42 affects the setting calculation of the actual job. Specifically, the update timing designation unit 41 acquires an update from the setting computer 23 of the actual job. When the parameter selected by the parameter selection unit 42 is used, the load given to the setting computer 23 is calculated. Further, the update timing designation unit 41 confirms the load status of the setting computer 23. In accordance with these circumstances, the update timing designation unit 41 confirms that even if a load due to the parameter acquisition occurs, the calculation of the actual work setting is not affected. When it is judged that the parameter update does not affect the setting calculation of the actual job, the processing of step S139 is performed. When it is judged that the parameter update affects the setting calculation of the actual job, the processing of step S138 is performed.

In step S138, it is determined whether or not the number of executions of the determination processing of step S137 is less than the upper limit number of times. When the determination condition is satisfied, the processing of step S137 is performed after the specified time has elapsed. When the determination condition is not established, the processing of the present routine is ended.

In step S139, the parameter copying unit 43 updates the model parameter selected by the update parameter selection unit 42 to the same value as the latest parameter used by the setting computer 23 of the actual job.

Fig. 14 is a flow chart showing a procedure for reviewing the alloy composition and manufacturing conditions by the rolling simulation device 24.

First, in step S140, the parameter update unit 33 updates all the model parameters at the time of regular repair. The processing in step S141 is the same as the processing in steps S131 and S132 of Fig. 13 described above.

In step S142, the parameter update unit 33 updates the mechanical constant associated with the roller and all the learning items. The processing in step S142 is the same as the processing in steps S133 and S134 of Fig. 13 described above.

In step S143, the user uses the calender simulation package. Set the output of the device to 24 and enter the simulation conditions. Specifically, the user inputs the initial flat embryo information (size, alloy composition) and various target values (heating furnace extraction target temperature, finish rolling inlet target temperature, finishing rolling exit target) of the virtual metal for simulation, as needed. Temperature, coiling target temperature, rough rolling outlet side target plate thickness, rough rolling outlet side target plate width, target plate width, target plate thickness, target crown height ratio, target flatness, etc. Enter detailed conditions as needed (eg heating furnace flat embryo heating mode, rough outlet side target temperature, reduction of each channel or reduction ratio, plate speed or acceleration rate, cooling mode at the delivery station, various sprayers) Setting, finish rolling and rolling supplier and workpiece roll replacement, etc.). The input simulation condition is set in the simulation condition setting unit 31.

In step S144, the parameter update unit 33 updates the learning item and the adjustment item related to the simulation condition before the execution of the simulation calculation. Specifically, the update parameter selection unit 42 selects the learning item and the adjustment item related to the simulation condition as the model parameter to be updated. The parameter copying unit 43 updates the selected model parameter to the same value as the latest parameter for the actual work.

In step S145, the virtual rolling line setting calculation unit 32 calculates a set value and each time of each processing of the virtual metal material by a virtual rolling line in accordance with the set simulation condition using the processing model, the transfer model, and the temperature model. The size, position, and temperature of the metal material. Further, the virtual rolling line setting calculation unit 32 uses the material model to input the processing history record of the virtual metal to be given and the temperature history record information as input values to predict the final product material. In addition, the use of metal tissue prediction mode Type to predict metal structure changes in imaginary calendering of hypothetical metals. Further, using the mechanical property prediction model, the structure and alloy composition of the finally calculated virtual metal product are used as input values to predict the mechanical properties such as the tensile stress and the tensile strength.

In step S146, the user confirms the quality of the virtual metal product based on the calculation result in step S145. In step S147, the user confirms the set value of each process. Further, in step S148, the simulation conditions are changed as needed, and the processes of steps S144 to S147 are repeatedly performed. In step S149, the user reviews whether the simulation result is applicable to the actual work.

According to the above sequence, the actual work calendering is not affected, and the simulation for simulating the actual work calendering can be performed. Further, by changing the simulation conditions and repeatedly performing the above simulation, and analyzing the results, it is possible to obtain a policy of improving the heating, rolling, and cooling conditions or the composition of the flat metal alloy in the actual work.

1‧‧‧calendering line

23‧‧‧Set computer

24‧‧‧Depression simulator

31‧‧‧ Simulation Condition Setting Department

32‧‧‧False rolling line setting calculation section

33‧‧‧Parameter Update Department

Claims (3)

A calendering simulation device is a calendering simulation device connected to a calendering system, the calendering system includes a calendering line, an actuator group that heats, calenders, cools, and transports a metal material, and detects the actuator a sensor group that controls the actual value of the group and the actual value of the metal material; and a setting computer that calculates a control target value of the actuator group and/or a state prediction value of the metal material; the setting computer system: There is a first model formula which exhibits a model of a physical phenomenon of each process of heating, rolling, cooling, and transport in the rolling line, and uses a function of input variables and model parameter groups as inputs. The present invention calculates the control target value of the actuator group and the state predicted value of the metal material by the first model formula, so as to achieve processing conditions related to product quality and/or working conditions in actual work. Comparing the control target value and the state prediction value with the aforementioned control actual value detected by the sensor group and the foregoing The model value parameter group of the first model formula is updated at any time, and the rolling simulation device includes an analog condition setting unit that heats, rolls, and cools the virtual metal material by the rolling line. Simulated conditions related to product quality and/or operating conditions in the imaginary operation of the transfer; The virtual rolling line setting calculation unit has a second model equation similar to the first model formula, and calculates the control target value of the actuator group and the virtual imagination by the second model formula to achieve the simulation condition. The state update value of the metal material; and the parameter update unit, when the model parameter group of the first model formula is updated, update the model parameter of the second model formula according to the model parameter group of the first model formula group. The rolling simulation device according to the first aspect of the invention, wherein the parameter updating unit includes: an update timing designating unit that specifies a timing at which calculation is not performed by the setting computer in an actual operation; and the parameter copying unit is In the above sequence, the model parameter group of the first model formula is copied to the model parameter group of the second model formula. The rolling simulation device according to the first aspect of the invention, wherein the parameter updating unit includes: an update parameter selection unit that selects the virtual rolling line setting calculation unit among the model parameter groups of the second model formula; And calculating a model parameter group of a part of the required model by using the model of the simulation condition; and the parameter copying unit is only for the model parameter group of the part selected by the update parameter selecting unit, from the aforementioned first model formula The model parameter group is copied.