CN109425439B - Steel casting interface molten steel temperature drop online prediction system and prediction method thereof - Google Patents
Steel casting interface molten steel temperature drop online prediction system and prediction method thereof Download PDFInfo
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- CN109425439B CN109425439B CN201710738908.6A CN201710738908A CN109425439B CN 109425439 B CN109425439 B CN 109425439B CN 201710738908 A CN201710738908 A CN 201710738908A CN 109425439 B CN109425439 B CN 109425439B
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- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K7/00—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements
- G01K7/02—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements using thermoelectric elements, e.g. thermocouples
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- B22—CASTING; POWDER METALLURGY
- B22D—CASTING OF METALS; CASTING OF OTHER SUBSTANCES BY THE SAME PROCESSES OR DEVICES
- B22D11/00—Continuous casting of metals, i.e. casting in indefinite lengths
- B22D11/16—Controlling or regulating processes or operations
- B22D11/18—Controlling or regulating processes or operations for pouring
- B22D11/181—Controlling or regulating processes or operations for pouring responsive to molten metal level or slag level
- B22D11/182—Controlling or regulating processes or operations for pouring responsive to molten metal level or slag level by measuring temperature
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Abstract
The invention discloses a steel-casting interface molten steel temperature drop online prediction system and a prediction method thereof, wherein the steel-casting interface molten steel temperature drop online prediction system comprises a steel ladle management information system, a molten steel temperature drop calculation model and an online temperature measurement system, wherein the molten steel temperature drop calculation model and the online temperature measurement system are combined and carry out coupled calculation, so that the temperature drop condition of all steel ladle molten steel is predicted in real time; the steel ladle management information system comprises a steel plate baking system, a steel ladle plan management system and a steel ladle state system; the on-line temperature measurement system comprises a thermocouple sensor, a temperature acquisition unit, a main control unit and a steel ladle temperature measurement database unit, wherein the thermocouple sensor is arranged on a steel ladle lining, the thermocouple sensor is connected with a receiving end of the temperature acquisition unit, and a transmitting end of the temperature acquisition unit is connected with a receiving end of the steel ladle temperature measurement database unit. The method solves the problems that the tapping temperature is too high and the calculation model correction data is limited due to rigid superposition of temperature drop of each procedure in the traditional tapping temperature setting.
Description
Technical Field
The invention relates to a prediction system for interface temperature drop in the steel industry, in particular to an online prediction system for steel casting interface molten steel temperature drop and a prediction method thereof.
Background
Modern steelmaking is centered on continuous casting, and the traditional tapping temperature setting process is as follows: and the continuous casting station estimates the value of rigid superposition to formulate the tapping temperature of the molten steel of the converter or the electric furnace according to the liquidus temperatures of different steel grades and the states of production and equipment through temperature drops of different procedures. In order to stabilize and continue production, the formulation of tapping temperature is generally high, the energy cost accounts for about 30% of the steel manufacturing cost, especially in smelting areas, energy consumption reduction becomes one of important means for cost reduction and efficiency improvement of steel companies, the tapping temperature is reduced by 0.5-3 yuan per ton of steel every time the tapping temperature is reduced by 1 ℃, the reduction of the tapping temperature is an important content for reducing the cost of steel making procedures, and the reduction of rigid superposition is one of approaches.
If the rigid temperature superposition of each process is to be reduced, the molten steel temperature drop condition of each station needs to be accurately and precisely predicted, and the aim of reducing the tapping temperature is achieved. With the development of informatization, a series of commercialized ladle informatization management systems are developed at home and abroad, and the ladle informatization management systems mainly comprise ladle position tracking, ladle number identification, ladle basic information management, ladle optimization and matching management, ladle hot repair management, ladle cold repair management, ladle turnover inspection management, ladle baking management and ladle production plan management. Typical representative systems include an X-PACT @ ladle management system developed by Simacre corporation, and a ladle integrated management system developed by West letter software and Chinese and Meta group in dispute. On the basis, the Beijing university of science and technology proposes a system to timely acquire the thermal state information of the steel ladle based on the real-time tracking of the steel ladle, and designs a relatively accurate molten steel temperature compensation value through a method of off-line numerical simulation and field data verification, thereby providing a basis for reducing the tapping temperature of a converter and developing a molten steel accurate reservation subsystem.
The method of off-line numerical model calculation and test temperature measurement correction is adopted, and the rigid superposition of temperature is reduced, including the calculation of the influence of baking temperature, the influence of thermal cycle period and the temperature drop of molten steel in the steel ladle heat radiator. The following disadvantages exist at present:
1) the correction of ladle heat loss calculation is difficult, especially the heat dissipation of the upper surface of a ladle at a continuous casting station;
2) the acquisition of the temperature measurement data of the refractory material of the test steel ladle is limited, and the whole process of tracking the temperature measurement data of the embedded thermocouple is difficult to achieve.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an online prediction system and a prediction method for steel-casting interface molten steel temperature drop, and solves the problems that the steel-casting temperature is higher and calculation model correction data is limited due to rigid superposition of temperature drops of all working procedures in traditional steel-casting temperature formulation.
In order to achieve the purpose, the invention adopts the following technical scheme:
on one hand, the steel casting interface molten steel temperature drop online prediction system comprises a steel ladle management information system, a molten steel temperature drop calculation model and an online temperature measurement system, wherein the molten steel temperature drop calculation model and the online temperature measurement system are combined and subjected to coupled calculation, so that the temperature drop condition of all steel ladle molten steel is predicted in real time;
the steel ladle management information system comprises a steel plate baking system, a steel ladle plan management system and a steel ladle state system;
the on-line temperature measurement system comprises a thermocouple sensor, a temperature acquisition unit, a main control unit and a steel ladle temperature measurement database unit, wherein the thermocouple sensor is arranged on a steel ladle lining, the thermocouple sensor is connected with a receiving end of the temperature acquisition unit, and a transmitting end of the temperature acquisition unit is connected with a receiving end of the steel ladle temperature measurement database unit.
The ladle lining comprises a heat insulating layer and a permanent layer.
The heat insulating layer comprises a heat insulating layer cold surface, and the permanent layer comprises a permanent layer hot surface and a permanent layer cold surface.
And a wireless signal communication mode is adopted between the transmitting end of the temperature acquisition unit and the receiving end of the ladle temperature measurement database unit.
The wireless signal communication mode is a wireless ZigBee module.
On the other hand, the online prediction method for the temperature drop of the steel-cast interface molten steel comprises the following steps:
s1, establishing an online temperature measurement system to form a steel ladle temperature measurement database unit;
s2, preliminarily predicting the temperature drop condition of each procedure of the steel ladle by using the molten steel temperature drop calculation model, and simulating and correcting the procedures;
s3, performing more accurate temperature drop calculation of each procedure of the steel ladle by adopting a coupled calculation of the molten steel temperature drop calculation model and data acquired by an online temperature measurement system;
and S4, acquiring relevant data of online heat dissipation and molten steel temperature of each procedure, correcting an online molten steel temperature drop calculation model, and combining the data of the online heat dissipation and the molten steel temperature drop on the basis of a steel ladle management information system so as to predict the molten steel temperature drop of the steel casting interface.
In step S1, the establishing of the online temperature measurement system specifically includes:
s1.1, embedding thermocouple sensors in a heat insulation layer and a permanent layer of a steel ladle lining;
s1.2, fixing the temperature acquisition unit on a steel ladle or a steel ladle cover;
s1.3, the temperature acquisition unit processes data and sends the data to a receiving end of the steel ladle temperature measurement database unit through a transmitting end of the temperature acquisition unit;
and S1.4, forming a steel ladle temperature measurement database unit.
In step S2, it is necessary to perform simulation and correction for the following four aspects:
1) a ladle online baking model or a model waiting for steel receiving heat loss;
2) carrying out steel receiving-refining initial heat loss model and temperature drop prediction;
3) a heat dissipation model and temperature drop prediction of a refining station;
4) and (4) a heat dissipation model and temperature drop prediction of a casting station.
In step S3, the calculation model is:
In the above formula, T1Is the hot side thermocouple temperature, T, of the permanent layer2Is the temperature of the thermocouple of the cold side of the permanent layer, T3Temperature of the thermocouple on the cold side of the heat insulating layer, d1Thickness of the permanent layer, d2Is the thickness of the insulating layer, λ1Thermal conductivity of the permanent layer, λ2Thermal conductivity of the thermal insulation layer.
In the step S4, the main parameters of the steel-cast interface molten steel temperature drop output are predicted to include the temperature of each process node, the heat dissipation curve and the heat storage curve.
In the technical scheme, the online prediction system and the online prediction method for the temperature drop of the molten steel at the steel-casting interface provided by the invention also have the following beneficial effects:
1. the invention can provide the temperature change rule of the ladle lining in real time;
2. the method predicts the temperature drop in a coupling mode of an online temperature measurement method and a calculation model, and more accurately predicts the temperature drop of the molten steel;
3. according to the invention, the ladle information management system is combined with the online prediction model, so that flexible superposition of tapping temperature drop is realized, and a foundation is provided for realizing low-temperature tapping.
Drawings
FIG. 1 is a schematic view of the frame structure of the present invention;
FIG. 2 is a schematic diagram of the framework of the on-line temperature measurement system of the present invention.
FIG. 3 is a graph showing the temperature drop of molten steel in a ladle in a casting process according to the present invention;
FIG. 4 is a graph of predicted molten steel temperature versus predetermined temperature for the present invention.
Detailed Description
The technical scheme of the invention is further explained by combining the drawings and the embodiment.
Referring to fig. 1 to 2, the steel casting interface molten steel temperature drop online prediction system provided by the invention comprises a steel ladle management information system 1, a molten steel temperature drop calculation model 2 and an online temperature measurement system 3, on the basis of the steel ladle management information system 1, firstly, the online temperature measurement system 3 for steel ladle wireless transmission is established, then, the molten steel temperature drop calculation model 2 is established, the online temperature measurement system 3 and the molten steel temperature drop calculation model 2 are combined and subjected to coupled calculation, and finally, the steel casting interface molten steel temperature drop online prediction system 100 is established, so that an effective basis is provided for a team leader to establish the tapping temperature of a converter/electric furnace.
Preferably, the ladle management information system 1 includes a steel plate baking system 101, a ladle plan management 102, and a ladle status system 103.
Preferably, the online temperature measurement system 3 includes a thermocouple sensor 301 disposed in a ladle lining, a temperature acquisition unit 302, a main control unit 303, and a ladle temperature measurement database unit 304, the thermocouple sensor 301 is connected to a receiving end of the temperature acquisition unit 302, and a transmitting end of the temperature acquisition unit 302 is connected to a receiving end of the ladle temperature measurement database unit 304. The method is used for testing the temperature change rule of each layer of thermocouple of the ladle in the pouring process to obtain the heat loss condition of the ladle cover in the pouring process.
Preferably, the ladle lining comprises a heat insulating layer and a permanent layer.
Preferably, the heat insulating layer comprises a heat insulating layer cold side, and the permanent layer comprises a permanent layer hot side and a permanent layer cold side.
Preferably, a wireless signal communication mode is used between the transmitting end of the temperature acquisition unit 302 and the receiving end of the ladle temperature measurement database unit 304.
Preferably, the wireless signal communication mode is realized by adopting a wireless ZigBee module with low power consumption.
The invention provides an online prediction method for steel casting interface molten steel temperature drop, which comprises the following steps:
s1, establishing an online temperature measurement system to form a ladle temperature measurement database unit, and acquiring a temperature change rule of a ladle lining in real time;
s2, preliminarily predicting the temperature drop condition of each procedure of the steel ladle by using the molten steel temperature drop calculation model, and simulating and correcting the procedures;
s3, performing more accurate temperature drop calculation of each procedure of the steel ladle by adopting a molten steel temperature drop calculation model and data coupling calculation acquired by an online temperature measurement system, so that more accurate prediction of the temperature drop condition of each procedure of the steel ladle can be realized, and the temperature drop condition of the molten steel of the steel ladle can be predicted in real time;
and S4, acquiring relevant data of online heat dissipation and molten steel temperature of each process, correcting an online molten steel temperature drop calculation model, and combining the data of the online heat dissipation and the molten steel temperature drop on the basis of a steel ladle management information system to predict the steel temperature drop of a steel casting interface and predict the temperature drop of all running steel ladles of a steel plant in real time.
Preferably, in step S1, the establishing of the online temperature measuring system specifically includes:
s1.1, embedding thermocouple sensors in a heat insulation layer and a permanent layer of a steel ladle lining;
s1.2, fixing the temperature acquisition unit on a steel ladle or a steel ladle cover;
s1.3, the temperature acquisition unit processes data and sends the data to a receiving end of the steel ladle temperature measurement database unit through a transmitting end of the temperature acquisition unit;
and S1.4, forming a steel ladle temperature measurement database unit.
Preferably, in step S2, the simulation and correction are performed according to the following four aspects:
1) a ladle online baking model or a model waiting for steel receiving heat loss;
2) carrying out steel receiving-refining initial heat loss model and temperature drop prediction;
3) a heat dissipation model and temperature drop prediction of a refining station;
4) and (4) a heat dissipation model and temperature drop prediction of a casting station.
Preferably, in step S3, the real-time temperatures of the thermal insulation layer and the permanent layer transmitted by the temperature acquisition unit are used for the boundary input of the heat flow calculation model, so as to calculate the heat flow simulation between the ladle permanent layer and the thermal insulation layer, and monitor the heat storage state of the refractory material. The calculation model is as follows:
In the above formula, T1Is a permanent layer hot faceTemperature of thermocouple, T2Is the temperature of the thermocouple of the cold side of the permanent layer, T3Temperature of the thermocouple on the cold side of the heat insulating layer, d1Thickness of the permanent layer, d2Is the thickness of the insulating layer, λ1Thermal conductivity of the permanent layer, λ2Thermal conductivity of the thermal insulation layer.
Preferably, in the step S4, the main parameters for predicting the steel-casting interface molten steel temperature drop output include the temperature of each process node, the heat dissipation curve and the heat storage curve.
The main input, output and correction data of the steel casting interface molten steel temperature drop online prediction system are shown in the following table 1:
TABLE 1
The main influence parameters of the temperature drop of the molten steel are as follows:
1) the influence of steel grade on temperature drop;
2) the influence of refractory erosion on heat loss and temperature drop;
3) the law of influence of the ambient temperature on heat loss and temperature drop;
4) influence of the thermal state of the steel ladle before steel connection on heat loss and temperature;
5) and (3) measuring physical property parameters: the heat conductivity of the covering agent at different temperatures, and the heat capacity, density and heat conductivity of the casting material and the working brick.
Basic assumption of a heat dissipation and temperature drop calculation model is as follows:
1) the fluid is incompressible;
2) two-dimensional axial symmetry;
3) the latent heat of fusion of the capping agent is ignored.
The calculation region comprises solid and fluid, the liquid level descending process of the ladle pouring process is simulated by adopting dynamic grid calculation, as shown in figure 4, the temperature descending process of the molten steel of the ladle in the pouring process is obtained by utilizing test temperature measurement data and model calculation, and the temperature of the molten steel is reduced from 1560 ℃ to 1535 ℃ and is reduced by 25 ℃ in the continuous descending process of the liquid level of the ladle for 50 min. The last 10min of the casting process, the temperature of the molten steel is reduced from 1543 ℃ to 1535 ℃ by 8 ℃.
Acquiring relevant data such as online heat dissipation, molten steel temperature and the like, and correcting an online calculation model; on the basis of a steel ladle information management system, the temperature drop of the steel liquid at the steel casting interface is predicted by further combining online heat dissipation and the temperature drop data of the steel liquid. The output main parameters comprise a change rule of the corresponding proportion of displaying the heat dissipation and heat storage of the steel ladle; the predicted temperature curve of each node, as shown in FIG. 4, the predicted and predetermined curves of the molten steel temperature mainly show the temperature nodes required by the temperature regime of the steel grade, where T1As the tapping temperature, T2For refining the incoming temperature, T3For refining the temperature, T4Casting temperature for continuous casting, T5Is the liquidus temperature.
The invention can change the rigid superposition of the traditional steel tapping into the flexible superposition, and provides guarantee for realizing the low-temperature steel tapping in steel making.
It should be understood by those skilled in the art that the above embodiments are only for illustrating the present invention and are not to be used as a limitation of the present invention, and that changes and modifications to the above described embodiments are within the scope of the claims of the present invention as long as they are within the spirit and scope of the present invention.
Claims (9)
1. The steel casting interface molten steel temperature drop online prediction system is characterized by comprising a steel ladle management information system, a molten steel temperature drop calculation model and an online temperature measurement system, wherein the molten steel temperature drop calculation model and the online temperature measurement system are combined and subjected to coupled calculation, so that the temperature drop condition of all molten steel ladles is predicted in real time;
the steel ladle management information system comprises a steel plate baking system, a steel ladle plan management system and a steel ladle state system;
the on-line temperature measuring system comprises a thermocouple sensor arranged on the ladle lining, a temperature acquisition unit, a main control unit and a ladle temperature measuring database unit, wherein the thermocouple sensor is connected with the receiving end of the temperature acquisition unit, the transmitting end of the temperature acquisition unit is connected with the receiving end of the ladle temperature measuring database unit,
the steel-casting interface molten steel temperature drop online prediction system executes the following operations:
s1, establishing an online temperature measurement system to form a steel ladle temperature measurement database unit;
s2, preliminarily predicting the temperature drop condition of each procedure of the steel ladle by using the molten steel temperature drop calculation model, and simulating and correcting the procedures;
s3, performing more accurate temperature drop calculation of each procedure of the steel ladle by adopting a coupled calculation of the molten steel temperature drop calculation model and data acquired by an online temperature measurement system;
s4, acquiring relevant data of online heat dissipation and molten steel temperature of each procedure, correcting an online molten steel temperature drop calculation model, combining the data of the online heat dissipation and the molten steel temperature drop on the basis of a steel ladle management information system so as to predict the molten steel temperature drop of a steel casting interface,
in step S2, it is necessary to perform simulation and correction for the following four aspects:
1) a ladle online baking model or a model waiting for steel receiving heat loss;
2) carrying out steel receiving-refining initial heat loss model and temperature drop prediction;
3) a heat dissipation model and temperature drop prediction of a refining station;
4) and (4) a heat dissipation model and temperature drop prediction of a casting station.
2. The system for on-line prediction of steel-casting interface molten steel temperature drop of claim 1, wherein the ladle lining comprises a heat insulating layer and a permanent layer.
3. The system of claim 2, wherein the thermal insulation layer comprises a cold side of the thermal insulation layer, and the permanent layer comprises a hot side of the permanent layer and a cold side of the permanent layer.
4. The on-line steel-casting interface molten steel temperature drop prediction system of claim 1, wherein a wireless signal communication mode is adopted between the transmitting end of the temperature acquisition unit and the receiving end of the steel ladle temperature measurement database unit.
5. The steel-casting interface molten steel temperature drop online prediction system of claim 4, wherein the wireless signal communication mode is a wireless ZigBee module.
6. The method for predicting the temperature drop of the molten steel in the steel-casting interface on line is characterized by comprising the following steps of:
s1, establishing an online temperature measurement system to form a steel ladle temperature measurement database unit;
s2, preliminarily predicting the temperature drop condition of each procedure of the steel ladle by using the molten steel temperature drop calculation model, and simulating and correcting the procedures;
s3, performing more accurate temperature drop calculation of each procedure of the steel ladle by adopting a coupled calculation of the molten steel temperature drop calculation model and data acquired by an online temperature measurement system;
s4, acquiring relevant data of online heat dissipation and molten steel temperature of each procedure, correcting an online molten steel temperature drop calculation model, combining the data of the online heat dissipation and the molten steel temperature drop on the basis of a steel ladle management information system so as to predict the molten steel temperature drop of a steel casting interface,
in step S2, it is necessary to perform simulation and correction for the following four aspects:
1) a ladle online baking model or a model waiting for steel receiving heat loss;
2) carrying out steel receiving-refining initial heat loss model and temperature drop prediction;
3) a heat dissipation model and temperature drop prediction of a refining station;
4) and (4) a heat dissipation model and temperature drop prediction of a casting station.
7. The method for predicting the temperature drop of the molten steel in the steel-cast interface of claim 6, wherein in the step S1, the establishing of the online temperature measuring system comprises the following specific steps:
s1.1, embedding thermocouple sensors in a heat insulation layer and a permanent layer of a steel ladle lining;
s1.2, fixing the temperature acquisition unit on a steel ladle or a steel ladle cover;
s1.3, the temperature acquisition unit processes data and sends the data to a receiving end of the steel ladle temperature measurement database unit through a transmitting end of the temperature acquisition unit;
and S1.4, forming a steel ladle temperature measurement database unit.
8. The method for on-line prediction of steel-casting interface molten steel temperature drop of claim 6, wherein in step S3, the calculation model is:
In the above formula, T1Is the hot side thermocouple temperature, T, of the permanent layer2Is the temperature of the thermocouple of the cold side of the permanent layer, T3Temperature of the thermocouple on the cold side of the heat insulating layer, d1Thickness of the permanent layer, d2Is the thickness of the insulating layer, λ1Thermal conductivity of the permanent layer, λ2Thermal conductivity of the thermal insulation layer.
9. The method for on-line prediction of steel-cast interface molten steel temperature drop of claim 6, wherein in step S4, the main parameters for predicting steel-cast interface molten steel temperature drop output include temperature of each process node, heat dissipation and heat storage curves.
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