CN102527971A - Online forecasting method for internal crack defect of casting blank - Google Patents
Online forecasting method for internal crack defect of casting blank Download PDFInfo
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Abstract
An online forecasting method for an internal crack defect of a casting blank belongs to the field of metal casting and comprises a network composed of a computer of L3, a computer of L2 and a computer of L1 and data transmission among the computers, wherein on the basis of the existing computer of L2 or the same control level, a model computer is arranged to obtain the internal stress strain information of the casting blank by real-time online analog computation of cooling and solidifying process of the casting blank, and then forecasts the internal crack defect of the casting blank in real time according to the variation tendency of the strain; then the quality information of the casting blank in the production process is timely transmitted to the cutting computer of L1 which is used for optimizing and controlling the cutting process of the casting blank with the defect; the quality control accuracy of a product and the product percent of pass are increased, the percent of pass and the commercial grade of the product are increased, and the whole economic benefit of an enterprise is further increased. Therefore, the online forecasting method for the internal crack defect of the casting blank can be widely applied to optimizing/control field of the cutting process of the casting blank during the production of slab continuous casting.
Description
Technical Field
The invention belongs to the field of metal casting, and particularly relates to an online forecasting/control method for casting blank internal quality defects in a continuous casting production process.
Background
In the continuous casting process, the casting blank can be deformed under the action of various external forces, and when the slab passes through the bending section, the slab can be subjected to the action of bending stress; when the slab passes through the correction segment, the slab is under the action of correction stress; under the action of the hydrostatic pressure of molten steel, the casting blank can bulge and deform. Under the action of these external forces, the continuously cast slab generates a certain strain, and if the accumulated strain exceeds the critical strain, internal cracks (referred to as internal cracks) occur.
Internal cracking is a common quality defect of a casting blank, and once formed, the internal cracking has great influence on subsequent processing and the comprehensive performance of products. Severe strand internal cracking can lead to strip delamination and even strip breakage during hot rolling.
In general, internal defects of a cast slab always exist once formed, and are difficult to eliminate in a post-processing process.
Therefore, the control of the internal quality of the casting blank can only be carried out in the continuous casting production process, and the occurrence rate of the internal defects of the casting blank is continuously reduced by improving the process and the operation level.
However, the causes of the continuous casting defects are very complex, involve a very large number of factors, and sometimes these factors are interwoven together, making the causes of the defects difficult to define accurately.
When internal crack defects form, the influence of the defects on subsequent processing and product performance is generally reduced through optimized cutting of the casting blank. For example, if there is an internal defect in a partial region of the head end of the cast slab, the defective region can be cut off by optimizing the cutting, thereby ensuring the overall quality of the remaining slab.
However, when the cast slab has an internal crack, the defect portion is surrounded by the solidified slab shell, and online detection cannot be performed.
Conventionally, after the cast slab is completely cut, a sample is taken from the head or the tail of the cast slab, and then the cast slab is checked for internal cracking through a low-power test. Since the low-power test period is generally about 2 days, this can seriously affect the logistic connection between continuous casting and hot rolling, and in practice, all the casting blanks cannot be sampled and tested.
For these reasons, people have been exploring how to predict defects in a cast slab.
The defect prediction has two functions: when the defects of the casting blank occur, the forecast result provides information for field operation engineers or process personnel, and the control parameters of the production process are adjusted in time under possible conditions, so that the duration of the defects of the casting blank is shortened as much as possible; according to the forecast information of the defects of the casting blank, the cutting process of the defective casting blank is controlled and optimized, and the product percent of pass is improved.
Regarding a method for predicting defects of a casting blank, chinese patent publication No. CN1269595C, 8/16/2006, discloses a method for predicting longitudinal cracks on the surface of a casting blank due to abnormal cooling of a mold, in which at least three rows of transverse thermocouples and at least three longitudinal thermocouples are embedded below the liquid level of molten steel in the mold, and these temperatures are read in by a data acquisition system, and data analysis is performed. The data analysis step at least comprises: under the condition of stable pulling speed, the temperature of a certain thermocouple in a certain row suddenly drops, and the speed reaches more than 3 ℃/s; the temperature of two thermocouples in the same row under the thermocouple also successively has a descending trend with the speed of more than 3 ℃/s, and the product of the time difference of the temperature of two adjacent thermocouples starting to descend and the instant pulling speed is exactly equal to the distance between the two thermocouples; the temperature of the three thermocouples in the row changes with time in a consistent mode, and the time for the temperature of the lower row of thermocouples to continuously decrease is not less than the time for the temperature of the upper row of thermocouples to continuously decrease. Therefore, according to the technical scheme, a certain number of thermocouples are arranged at a certain position of the crystallizer, so that the temperature fluctuation in the crystallizer is monitored in real time. When the temperature fluctuation exceeds a certain range and meets a certain condition, the occurrence of the longitudinal crack defect of the casting blank can be judged.
The above method is applicable only to defects on the surface of a cast slab caused by abnormal fluctuation of the temperature of the mold.
According to related researches, the main reasons for triggering the internal crack defect are as follows: the deformation caused by the action of external force on a solid-liquid interface in the incompletely solidified casting blank exceeds a critical strain value, wherein the strain comprises bending strain, straightening strain, bulging strain and the like. However, although the strain is closely related to the crack defect in the cast slab, the strain itself is difficult to detect.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an online forecasting method for the internal crack defect of a casting blank, which obtains the stress-strain information of the interior of the casting blank by simulating and calculating the cooling and solidifying process of the casting blank in real time and online, and then forecasts the internal crack defect of the casting blank according to the change trend of strain. And the casting blank quality information in the production process is timely transmitted to a cutting L1 computer, which is used for optimizing and controlling the cutting process of the defective casting blank, and can improve the control precision of the product quality and the product percent of pass.
The technical scheme of the invention is as follows: the method comprises a network formed by an L3-level computer, an L2-level computer and an L1-level computer and data transmission among the computers, wherein the L3-level computer is responsible for issuing a production plan instruction, the L2-level computer is responsible for determining various control parameters in the production process according to the production plan and executing the control parameters by an L3-level computer, the L3-level computer executes a control instruction issued by the L2-level computer or input by an operator and directly or indirectly controls related equipment of the casting machine, the L3-level computer at least comprises a public L1 computer, a casting L1 computer and a cutting L1 computer, and the method is characterized by at least comprising the following steps:
A. setting a model computer in the existing L2 computer or on the same control level;
B. the L2-level computer collects various process and control parameters completely in the casting process through the L1-level computer and then sends the parameters to the model computer according to a certain interval period;
C. the model computer receives the process and control parameters in the casting blank production process in real time and on line and determines the boundary condition of the casting blank heat dissipation calculation;
D. the model computer dynamically calculates the heat dissipation process of the casting blank and the outside based on the mathematical model description of the heat transfer process of the casting blank to obtain the temperature fields of the inside and the outside of the casting blank;
E. the model computer dynamically calculates the cooling and solidification process of the casting blank to obtain the solidification thickness information of each slice position of the casting blank;
F. the model computer dynamically analyzes the stress change of the casting blank in the moving process, and calculates bulging strain, straightening strain and dislocation strain of the casting blank caused by the action of external force to obtain the total strain distribution of the casting blank;
G. the model computer predicts whether the internal crack occurs or not by judging whether the strain exceeds a critical strain value or not according to the change trend of the strain, and predicts the internal crack defect of the casting blank in real time;
H. if the casting blank is judged to have internal cracks, the model computer calculates specific defect information, the information is related to specific position information of the plate blank, and the information is transmitted to a cutting computer through an L2-level computer to optimally control the cutting process of the casting blank;
I. the cutting computer adjusts the cutting position of the casting blank, and directly cuts off the defective blank after optimizing cutting for the blank with the center crack near the head or tail position of the preset blank; cutting the slab with the defect in the middle of the preset slab according to the preset position, attaching a defect mark to the cut slab, and degrading or changing the defect mark according to the requirement;
J. the steps are carried out on line in real time in the casting process of the casting blank.
Specifically, the model computer is a PC, an industrial personal computer, a single chip microcomputer or a virtual computer located in an L2-level computer.
The various process and control parameters in the casting process are related process parameters in the heat transfer process of the casting blank, and at least comprise steel grade, tundish molten steel temperature, thickness, drawing speed, width and cooling water flow; the model computer determines the boundary condition of the casting blank heat conduction calculation according to the data, and determines the total heat transferred from the casting blank to the outside in unit time; along with the movement of the physical position of the casting blank, the model computer periodically updates the initial value and the boundary condition of the casting blank heat transfer calculation.
The model computer firstly calculates the heat dissipation coefficient of the surface of the casting blank at each moment according to the cooling water quantity and the cooling air quantity, and then calculates the heat dissipated to the outside from the surface of the casting blank in unit time on the basis of the heat dissipation coefficient, so as to obtain the temperature fields inside and outside the casting blank according to the physical property parameters of the steel.
Further, in the cooling process, the heat quantity dissipated to the outside by the casting blank is calculated by adopting the following expression:
φ＝h(Us-Uw)(w/m2)
where phi is the intensity of outward heat dissipation per unit area, UsIs the surface temperature of the cast slab, UwIs the temperature of the cooling water, and h is the heat dissipation coefficient of the casting blank surface.
Further, the heat dissipation coefficient of the surface of the casting blank is calculated by the following expression:
h＝kwrwara
wherein w is the water flow density and rw is the water volume factor; a is gas density, ra is gas coefficient, and k is constant.
Further, the water flow density is calculated by taking a cooling area as a unit, calculating the total amount of water sprayed on the upper surface of a casting blank by the cooling area, and dividing the total amount of water sprayed on the upper surface of the casting blank by the area of the cooling area to obtain the water flow density; the calculation method of the gas volume density is the same as that of the water flow density.
Further, the model computer firstly calculates the solidification rate of each position on the casting blank, and then calculates the solidification thickness according to the solidification rate;
the calculation expression of the solidification rate is as follows:
wherein fs is the solidification rate of the cast slab, TlIs the liquidus temperature, T, of the steelsIs the solidus temperature, T, of the steelcIs the temperature on the center line of the plate blank;
and the model computer calculates the solidification rate of each position on the cross section of the casting blank by using the calculation expression, and then calculates the solidification thickness of each position.
The model computer respectively calculates bulging strain, straightening strain and dislocation strain based on the casting blank temperature field distribution and the solidification thickness information obtained by calculation, superposes the strains, and calculates the total strain at each casting blank slice position by taking a casting blank slice as a unit.
Further, the bulging strain is calculated by adopting the following expression:
in the formula:
εb(i) the method comprises the following steps Bulging strain, s, of the casting blank solidification interface at the ith rolli: casting blank solidification thickness l corresponding to the ith casting roll positioni: ith roller spacing, δi: amount of bulging deformation.
Further, the calculation formula of bulging deformation of the casting blank is as follows:
for a slab, η α is 1; p: the hydrostatic pressure of molten steel borne by the casting rolls; v. ofg: the blank drawing speed; e: the coefficient of elasticity.
The calculation formula of the elastic coefficient is as follows:
wherein, TSTo the setting temperature, TMIs the average temperature.
The calculation formula of the average temperature is as follows:
wherein, TSTo the setting temperature, TfIs the surface temperature.
Further, the straightening strain calculation formula of the casting blank is as follows:
in the formula:
si: the thickness of a casting blank solidified shell at the ith straightening roller;
d: the thickness of a casting blank;
Ri: the radius of the outer arc of the casting blank before the ith straightening roll;
Ri+1: casting blank outer arc radius after the ith straightening roll;
εu(i) the method comprises the following steps And straightening strain of the casting blank corresponding to the ith straightening roller.
The dislocation strain is the strain on a casting blank solidification interface caused by inaccurate alignment of the continuous casting pinch rolls, and the calculation formula is as follows:
wherein epsilonm(i)The strain generated on the solidification interface at the ith roller due to roller dislocation; deltamIs the amount of misalignment at the roller; siIs the thickness of the cast slab at the ith roll.
The model computer obtains the total strain distribution of the casting blank through the following steps:
and (3) taking the position of the casting roll as an index parameter, searching in all slices, finding out the slices with the same position, directly substituting the temperature information and the solidification thickness information of the slices into a strain formula for calculation, and calculating the total strain according to the casting roll after all strain indexes are calculated to obtain the current total strain distribution of the casting blank.
Or, the model computer obtains the total strain distribution of the casting blank by the following steps:
and taking the position of the casting roll as an index parameter, searching in all the slices, finding out two slices closest to the position of the casting roll, obtaining casting blank temperature and solidification thickness information corresponding to the position of the casting roll by linear interpolation according to the position of the casting roll, the positions of two adjacent slices in the front and back, and the temperature information and the solidification thickness information recorded on the two slices in the front and back, and bringing the casting blank temperature and the solidification thickness information into a strain formula for calculation, and calculating total strain according to the casting roll after all strain indexes are calculated to obtain the current total strain distribution of the casting blank.
More specifically, the steel types are classified in advance, critical strain values are set for each type of steel, the parameters are stored in a database of a model computer forecasting model, corresponding critical strain is indexed from the database according to the type of poured steel during model computer calculation, then the model computer judges the total strain of the casting blank corresponding to each casting roller in sequence from the outlet of a casting machine to the direction of a crystallizer, whether the total strain exceeds the total critical strain is judged, if the strain exceeds the critical strain value, the occurrence of an internal crack defect is judged, and the model computer records the occurrence position information of the defect.
The critical strain value range of the casting blank is between 0.5% and 0.8%, the limit strain which can be borne by the casting blank is related to the steel type, and the specific numerical value is obtained through a process test.
When the model computer judges that the casting blank has internal cracks, the specific position of the internal cracks is recorded, and the duration time of the internal cracks is tracked to finally determine the area covered by the internal cracks on the casting blank.
And after the model computer completes the calculation, the calculation result information is transmitted to a process computer for controlling the cutting of the casting blank through a network, and the casting blank is optimally cut according to the characteristics of the severity of the defect, the size of the region and the like, so that the yield of the product is improved.
Dividing the whole casting blank into a series of slices with the same area as the section area of the casting blank along the casting direction to form casting blank slices; the heat transfer calculation of the casting blank is carried out on the casting blank slices, and the calculation of a fixed time period is carried out; the model computer can obtain temperature information of any position of the casting blank through interpolation calculation according to the temperature field information of each casting blank slice; the calculation of the casting blank solidification thickness, the temperature field information and the solid phase temperature is also carried out on the casting blank slices.
And the mathematical model description of the casting blank heat transfer process comprises the solidification calculation of the continuous casting slab, the boundary condition of a temperature distribution equation and the initial condition for solving the temperature distribution equation.
The continuous casting slab solidification calculation is started from the crystallizer and ended before the continuous casting slab is taken out of the casting machine, and only the heat conduction in the thickness direction is considered for the slab, and the heat conduction in the casting direction and the width direction of the casting blank is not considered; the liquid phase initial temperature of the molten steel is equal to the tundish temperature; the cooling intensity is kept unchanged in the same cooling section of the continuous casting.
The solidification calculation of the continuous casting slab is described by the following expression:
wherein: x is the distance from the surface of the casting blank; t is casting start time; u (x, t) is the temperature distribution of the section of the casting blank; rho is density; c is specific heat; k is the thermal conductivity.
The boundary conditions of the temperature distribution equation are as follows:
cast sheet watchSurface temperature U (0, t) ═ Us，
Wherein, UsIs the surface temperature of the cast piece, h is the heat transfer coefficient, UwCooling water temperature, UextIs the ambient temperature, σ is the Stefan-Boltzmann constant, and ε is the jetness coefficient.
The initial conditions for solving the temperature distribution equation are as follows:
assuming that the time T of molten steel injection into the mold is 0, U (x, 0) is TTD；
Initial value of solidification thickness: x is the number ofs|t＝0＝0
Initial value of surface temperature: u shapes|x＝0＝TS
Wherein: t isTDThe tundish temperature and TS the solid phase temperature.
When the heat conduction equation and the boundary condition of the casting blank heat dissipation process are actually calculated, the equation is discretized and converted into a heat conduction equation in a differential format for solving.
The interval period is a time unit of a second level, and the range of the interval period is usually between 5 and 10 s.
Compared with the prior art, the invention has the advantages that:
1. the strain state of the casting blank is dynamically tracked and calculated through a model computer according to the current process data, and then the quality condition inside the casting blank is judged according to the change trend of the strain, so that the calculation result is strong in real-time performance and good in online synchronization performance;
2. for slabs with a central crack near the head or tail of the predetermined slab, the defective slab is directly cut off by optimized cutting. The slab is cut according to the preset condition for the defect in the middle of the preset slab, but the cut slab is marked with the defect and degraded or changed according to the requirement, so the method can effectively improve the product yield and the quality stability.
3. By adopting the method, the product quality of production enterprises is improved, the qualification rate and the commodity grade of the product are improved, and the overall economic benefit is further improved.
Drawings
FIG. 1 is a block diagram of the control method of the present invention;
FIG. 2 is a schematic view of the control system according to the present embodiment;
FIG. 3 is a schematic diagram of the relationship between slices and a casting blank;
fig. 4 is a schematic view of slice coordinate positioning.
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
In fig. 1, the technical scheme provides a method for online forecasting of the internal crack defect of a casting blank, which includes obtaining stress strain information inside the casting blank through online simulation calculation of a cooling and solidification process of the casting blank, and forecasting the internal crack defect of the casting blank according to a change trend of strain.
According to the technical scheme, the internal quality state of the casting blank is forecasted on line, the casting blank quality information in the production process is timely transmitted to the cutting computer, the cutting process of the defective casting blank is optimized and controlled, and the product quality control precision and the product percent of pass are improved.
The key steps of the technical scheme of the application comprise:
A. setting a model computer in the existing process control computer or on the same control level;
B. the process control computer collects various process and control parameters completely in the casting process through an L1-level computer and then sends the parameters to the model computer according to a certain interval period;
C. the model computer receives the process and control parameters in the casting blank production process in real time and on line and determines the boundary condition of the casting blank heat dissipation calculation;
D. the model computer dynamically calculates the heat dissipation process of the casting blank and the outside based on the mathematical model description of the heat transfer process of the casting blank to obtain the temperature fields of the inside and the outside of the casting blank;
E. the model computer dynamically calculates the cooling and solidification process of the casting blank to obtain the solidification thickness information of each slice position of the casting blank;
F. the model computer dynamically analyzes the stress change of the casting blank in the moving process, and calculates bulging strain, straightening strain and dislocation strain of the casting blank caused by the action of external force to obtain the total strain distribution of the casting blank;
G. the model computer predicts whether the internal crack occurs or not by judging whether the strain exceeds a critical strain value or not according to the change trend of the strain, and predicts the internal crack defect of the casting blank in real time;
H. if the casting blank is judged to have internal cracks, the model computer calculates specific defect information, the information is related to specific position information of the plate blank, and the cutting computer is issued by the process control computer to optimally control the cutting process of the casting blank;
I. the cutting computer adjusts the cutting position of the casting blank, and directly cuts off the defective blank after optimizing cutting for the blank with the center crack near the head or tail position of the preset blank; cutting the slab with the defect in the middle of the preset slab according to the preset position, attaching a defect mark to the cut slab, and degrading or changing the defect mark according to the requirement;
J. the steps are carried out on line in real time in the casting process of the casting blank.
The model computer is a PC, an industrial personal computer, a single chip microcomputer or a virtual computer in an L2-level computer.
Specifically, the method is based on numerical simulation, and through quantitative calculation of the heat transfer process of the casting blank, the temperature field change and the solidification thickness change of the continuous casting slab in the casting process are calculated in real time, and further the strain change of each position of the casting blank is calculated. Whether the internal cracking occurs is predicted by judging whether the strain exceeds a critical strain value, if so, specific information of the internal cracking defect is calculated, the information is associated with the slab and is transmitted to a process computer for controlling the cutting of the casting blank, and the process computer is used for optimizing and controlling the cutting process of the casting blank.
First, the calculation of the solidification of the continuously cast slab is discussed, starting from the crystallizer and ending before exiting the casting machine, which is basically a heat-conducting and heat-dissipating process whose metallurgical mechanism can be described by the following formula:
wherein: x is the distance (m) from the surface of the casting blank;
t is casting start time (min);
u (x, t) is the temperature distribution of the section of the casting blank;
rho is density (kg/m)3)；
c is the specific heat (J/(kg. DEG C.);
k is the thermal conductivity (KCal/(m.h.. degree. C)).
In the calculation, some reasonable assumptions need to be made according to actual situations.
For the slab, only the heat conduction in the thickness direction is considered, and the heat conduction in the casting direction and the width direction of the casting blank is not considered; the liquidus initial temperature of the molten steel is equal to the tundish temperature (the average temperature of the molten steel in the tundish); the cooling intensity is kept unchanged in the same cooling section of the continuous casting.
(1) The boundary conditions of the temperature distribution equation are:
surface temperature of cast piece U (0, t) is Us，
Wherein,
Usthe temperature of the surface of the cast piece is,
h is a coefficient of thermal conductivity,
Uwtemperature of cooling water
UextIs the ambient temperature
σ is the Stefan-Boltzmann constant, and ε is the jetness coefficient.
At the position of a casting blank thickness center x ═ Thick/2:
(2) solving the initial conditions of the temperature distribution equation:
assuming that the time T of molten steel injection into the mold is 0, U (x, 0) is TTD；
Initial value of solidification thickness: x is the number ofs|t＝0＝0
Initial value of surface temperature: u shapes|x＝0＝TS
Wherein: t isTDThe tundish temperature and TS the solid phase temperature.
The heat conduction equation and boundary conditions for describing the heat dissipation process of the casting blank are given above, and the equation needs to be discretized and converted into a heat conduction equation in a differential format for solving in actual calculation.
In addition, because the temperature information and the solidification thickness information of the continuous casting slab at all positions are calculated, the whole casting blank is divided into a series of slices along the casting direction for the convenience of computer solution.
The so-called "slice" can be regarded as a thin slice equal to the cross-sectional area of the cast slab, and the positional relationship and coordinate positioning of the slice and the cast slab are schematically shown in the attached fig. 3 and 4 of the specification.
Since both figures are represented by means and symbols commonly used in the art, the meaning and represented information will be fully understood by those skilled in the art and will not be described herein.
The chips are produced at the meniscus of the crystallizer and then move along with the cast slab, and are automatically destroyed after being discharged from the casting machine. And (4) performing heat transfer calculation of the casting blank on the slices, and periodically calculating. During casting, the temperature of the surface and the interior of the cast strand is continuously varied. Therefore, temperature information at any position of the cast slab can be obtained by interpolation calculation based on the temperature field information on each cast slab slice. The solidification thickness of the cast slab can be calculated from the temperature field information and the solid phase temperature, and all the calculations are also performed on the sliced piece of the cast slab.
Based on the casting blank state information obtained by the calculation, various strains generated when the casting blank is subjected to external force can be calculated according to a strain formula, and further, the quality condition in the casting blank is judged according to the variation trend of the strains.
The following gives a specific calculation procedure for defect prediction, which is repeated periodically:
a) collecting casting blank production process parameters and determining boundary conditions of casting blank heat dissipation calculation.
b) And dynamically calculating the heat dissipation process of the casting blank and the outside based on the mathematical model description of the heat transfer process of the casting blank to obtain the temperature fields of the inside and the outside of the casting blank.
c) And dynamically calculating the cooling and solidification process of the casting blank to obtain the solidification thickness information of each position of the casting blank.
d) And dynamically analyzing the stress change of the casting blank in the moving process, and calculating bulging strain, straightening strain and dislocation strain of the casting blank due to the action of external force to obtain the total strain distribution of the casting blank.
e) And predicting the internal crack defect of the casting blank according to the change trend of the strain.
f) And if the casting blank is judged to have internal cracks, calculating specific defect information, transmitting the specific defect information to a cutting computer, and optimally controlling the cutting process of the casting blank.
For step a), collecting process parameters related to the heat transfer process of the casting blank, including steel type, tundish molten steel temperature, thickness, drawing speed, width, cooling water flow and the like. According to the data, boundary conditions for the calculation of the heat transfer of the casting blank are determined, and the total heat transferred to the outside by the casting blank in unit time is determined. And updating the initial value and the boundary condition of the heat transfer calculation of the casting blank at fixed period along with the movement of the casting blank.
For the step b), the heat quantity dissipated to the outside by the casting blank during the cooling process can be calculated by the following formula:
φ＝h(Us-Uw)(w/m2) (4)
where phi is the intensity of outward heat dissipation per unit area, UsIs the surface temperature of the cast slab, UwIs the temperature of the cooling water, h is the heat dissipation coefficient of the casting blank surface, and is calculated by the following formula:
h＝kwrwara (5)
wherein w is the water flow density and rw is the water volume factor; a is gas density, ra is gas coefficient, and k is constant.
The water flow density is calculated by taking the cooling area as a unit, calculating the total water spray amount of a certain cooling area on the upper surface of the casting blank, and dividing the total water spray amount by the area of the cooling area to obtain the water flow density. The calculation method of the gas density is the same, and the description is not repeated here.
At each moment, the heat dissipation coefficient of the surface of the casting blank is firstly calculated according to the cooling water quantity and the cooling air quantity, then the heat dissipated from the surface of the casting blank in unit time is calculated on the basis of the heat dissipation coefficient, and further the internal and external temperature fields of the casting blank are obtained according to the physical property parameters of the steel type.
In step c), it is noted that the solidification of the steel does not simply change from liquid to solid, but as the temperature decreases, there is a two-phase region, which we usually refer to as "mushy zone". Below the solidus temperature of the steel grade, the molten steel can be completely transformed into a solid. When the solidification thickness of the casting blank is calculated, the solidification rate of each position on the casting blank is firstly calculated, and then the solidification thickness is calculated according to the solidification rate.
The formula for calculating the coagulation rate is:
wherein fs is the solidification rate of the cast slab, TlIs the liquidus temperature, T, of the steelsIs the solidus temperature, T, of the steelcIs the temperature on the centerline of the slab.
And calculating the solidification rate of each position on the cross section of the casting blank by using the calculation formula, and then calculating the solidification thickness of each position.
And d), respectively calculating bulging strain, straightening strain and dislocation strain based on the temperature field distribution and the solidification thickness information of the casting blank obtained by the previous calculation, and calculating the total strain of the casting blank at each position. Computationally, the bulge strain is calculated using:
in the formula:
εb(i) the method comprises the following steps Bulging Strain at casting blank solidification interface at ith roll (%)
si: casting blank solidification thickness (mm) corresponding to the ith casting roll position
li: distance between the ith roller (mm)
δi: deformation of drum belly (mm)
Among these parameters, the calculation formula of bulging deformation of a cast slab is:
for a slab, η α is 1;
p: the casting roller bears the ferrostatic pressure of kg/cm 2;
vg: the blank drawing speed is cm/min;
e: the coefficient of elasticity of the elastic material is,
TSto the setting temperature, TfIs the surface temperature, TMIs the average temperature of the molten steel, and is,
when the casting blank passes through the straightening area of the continuous casting machine, the casting blank at the position generates straightening strain under the action of the straightening stress. The straightening strain is related to the curvature radius of a straightening point of a continuous casting machine, and the calculation formula is as follows:
in the formula:
si: casting blank condensing shell thickness (mm) at the ith straightening roll
D: casting blank thickness (mm);
Ri: casting blank outer arc radius (mm) before ith straightening roll
Ri+1: casting blank outer arc radius mm behind ith straightening roll
εu(i) The method comprises the following steps Casting blank straightening strain (%)
The dislocation strain is the strain on the solidification interface of the casting blank caused by inaccurate alignment of the continuous casting pinch rolls, and the calculation formula is as follows:
wherein epsilonm(i)The strain generated on the solidification interface at the ith roller due to roller dislocation; deltamIs the amount of misalignment (mm) at the roller; siThe thickness (mm) of the cast slab at the ith roll.
And respectively calculating bulging strain, straightening strain and dislocation strain based on the strain calculation formula and the temperature field and solidification thickness information of the casting blank obtained by the calculation.
The specific method comprises the following steps: and taking the position of the casting roll as an index parameter, searching all the slices, and finding out the slice in the same position or finding out two slices closest to the position of the casting roll.
For the former case, directly substituting the temperature information and the solidification thickness information of the slice into a strain formula for calculation; in the latter case, linear interpolation is performed according to the casting roll position, the two adjacent front and rear slice positions, and the temperature information and the solidification thickness information recorded on the front and rear slices to obtain the casting blank temperature and solidification thickness information corresponding to the casting roll position, and the casting blank temperature and solidification thickness information is brought into a strain formula for calculation.
And after all the strain indexes are calculated, calculating the total strain according to the casting rolls to obtain the current total strain distribution of the casting blank.
For step e), the critical strain at which the slab cracks due to deformation under stress is generally between 0.5% and 0.8%. However, due to the difference of chemical components and mechanical properties, the ultimate strain that a casting blank can bear is related to the steel grade, and specific numerical values are obtained through process tests.
In practical application, steel grades are classified in advance, critical strain values are set for each steel grade, and the parameters are stored in a database of a forecasting model.
When the forecasting model is calculated, corresponding critical strain can be indexed from a database according to the casting steel grade. And then, sequentially judging the total strain of the casting blank corresponding to each casting roller from the outlet of the casting machine to the direction of the crystallizer, judging whether the total strain exceeds the total critical strain, if the strain exceeds the critical strain value, judging that the internal crack defect occurs, and recording the occurrence position information of the defect.
In step f), a section of area is affected by the internal crack of the casting blank caused by strain, so when the model judges that the internal crack occurs, the specific position where the internal crack occurs is recorded, and the duration time of the internal crack is tracked to finally determine the area covered by the internal crack on the casting blank. After the calculation is finished, the information is transmitted to a process computer for controlling the cutting of the casting blank through a network, the casting blank is optimally cut according to the characteristics of the severity of the defect, the size of the region and the like, and the yield of the product is improved.
Example (b):
a vertical bending type slab continuous casting machine in a certain steel mill has two flows, and the product specification is mainly 220mm multiplied by 1930 mm.
The structure of the production control system is shown in the attached figure 2 in the specification.
In the production process, the L3-level computer is responsible for issuing a production plan instruction, the L2-level computer is responsible for determining various control parameters in the production process according to the production plan, and the control parameters are executed by the L1-level computer; on the other hand, the L2 grade computer collects all kinds of technological and control parameters in the casting process completely through the L1 grade computer, and then sends the parameters to the model computer according to a certain period.
And the model computer carries out dynamic tracking calculation on the strain state of the casting blank according to the current process data.
When the model computer determines that the casting blank internal crack defect occurs, the position information of the defect is corresponding to a preset slab, then the information is sent to the L2-level computer, the L2-level computer sends the information to the cutting L1 computer, and the cutting position of the casting blank is adjusted according to the position of the defect, so that the qualified rate of casting blank products is improved.
To calculate the dynamic strain occurring at each position of the cast slab, the internal and external temperature fields and the solidification thickness information of the cast slab are obtained in real time, and they are obtained by calculating the heat transfer process of the cast slab.
The heat transfer calculation uses the heat transfer equation of equation (1), and the parameter information used for the calculation is as follows:
for a heat transfer calculation formula of an air cooling area, selecting a blackness coefficient epsilon to be 0.85; the heat dissipation coefficient of the casting blank surface was calculated using the following formula
h＝280.56w0.382a0.1373
Wherein w is calculated by using the actual amount of water sprayed onto the inner arc surface of the casting slab and the actual casting slab area covered by the sprayed water, and a is calculated by the same method.
Dividing and cutting the casting blank according to the standard of 50mm intervals, and selecting the interval period of model calculation for 8 s.
When the technical scheme of the application is applied, the following processes are periodically executed:
an L2-level computer (hereinafter referred to as L2) periodically collects process data information such as cooling water amount, air amount (gas spray control), casting speed, tundish temperature, crystallizer cooling water amount, and crystallizer inlet and outlet cooling water temperature difference of each cooling circuit from an L1-level computer.
According to the production process information input by L2, the temperature field and the solidification thickness at each position of the casting blank are dynamically calculated by using a heat transfer equation, wherein the solidification thickness refers to the vertical distance between the position and the surface of the casting blank, wherein fs calculated according to the formula (6) is 1.0 on the cross section of the casting blank.
And (4) dynamically calculating bulging strain, straightening strain and dislocation strain on all casting blank slices based on the formulas (7) to (10).
Since each strain occurs under a separate external force, the strains can be superimposed. Therefore, the total strain amount on each slab of the cast slab is calculated in units of slabs.
And (4) judging the strain on each slice from the outlet of the casting machine to the outlet of the crystallizer, and indexing the judged threshold value from the database according to the current casting steel type.
And if the total strain on the casting blank slice is larger than a critical threshold value, setting a strain abnormity mark.
And sequentially judging each casting blank slice, and setting a corresponding mark on each casting blank slice according to the comparison result of the total strain and the critical threshold.
If the strain of the casting blank is judged to exceed the critical value by the model in the last calculation period, and the strain of the casting blank is all normal in the current period, at the moment, the specific position of the strain abnormality can be determined according to the abnormality mark on the casting blank slice.
The starting and ending positions of the defects of the casting slab and the stream number are sent to a cutting L1 computer, and the abnormal mark on the casting slab is cleared.
And determining the defect occurrence position according to the model, and adjusting the cutting position of the casting blank by the cutting L1 computer.
After the method is used, the slab with the central crack near the head or the tail of the preset slab is directly cut off after optimized cutting. And cutting according to the preset rule when the defect in the middle of the preset slab occurs, and attaching a defect mark to the cut slab, and degrading or changing the defect according to the requirement.
According to the technical scheme, the cooling and solidifying process of the casting blank is simulated and calculated in real time and on line, the stress strain information inside the casting blank is obtained, and then the internal crack defect of the casting blank is forecast in real time according to the change trend of the strain. And then the casting blank quality information in the production process is timely transmitted to a cutting L1 computer, which is used for optimizing and controlling the cutting process of the defective casting blank, and can improve the control precision of the product quality and the product percent of pass. By using the method, the product qualification rate and the quality stability are improved, the qualification rate and the commodity grade of the product are improved, and further the overall economic benefit of an enterprise is improved.
The invention can be widely applied to the field of optimization/control of the cutting process of the casting blank in the slab continuous casting production process.
Claims (28)
1. An online forecasting method for casting blank internal crack defects comprises a network formed by an L3-level computer, an L2-level computer and an L1-level computer and data transmission among the computers, wherein the L3-level computer is responsible for issuing production plan instructions, the L2-level computer is responsible for determining various control parameters in a production process according to the production plan and executing the control parameters by an L3-level computer, the L3-level computer executes control instructions issued by the L2-level computer or input by an operator and directly or indirectly controls related equipment of a casting machine, the L3-level computer at least comprises a public L1 computer, a casting L1 computer and a cutting L1 computer, and the online forecasting method is characterized by at least comprising the following steps:
A. setting a model computer in the existing process control computer or on the same control level;
B. the process control computer collects various process and control parameters completely in the casting process through an L1-level computer and then sends the parameters to the model computer according to a certain interval period;
C. the model computer receives the process and control parameters in the casting blank production process in real time and on line and determines the boundary condition of the casting blank heat dissipation calculation;
D. the model computer dynamically calculates the heat dissipation process of the casting blank and the outside based on the mathematical model description of the heat transfer process of the casting blank to obtain the temperature fields of the inside and the outside of the casting blank;
E. the model computer dynamically calculates the cooling and solidification process of the casting blank to obtain the solidification thickness information of each slice position of the casting blank;
F. the model computer dynamically analyzes the stress change of the casting blank in the moving process, and calculates bulging strain, straightening strain and dislocation strain of the casting blank caused by the action of external force to obtain the total strain distribution of the casting blank;
G. the model computer predicts whether the internal crack occurs or not by judging whether the strain exceeds a critical strain value or not according to the change trend of the strain, and predicts the internal crack defect of the casting blank in real time;
H. if the casting blank is judged to have internal cracks, the model computer calculates specific defect information, the information is related to specific position information of the plate blank, and the cutting computer is issued by the process control computer to optimally control the cutting process of the casting blank;
I. the cutting computer adjusts the cutting position of the casting blank, and directly cuts off the defective blank after optimizing cutting for the blank with the center crack near the head or tail position of the preset blank; cutting the slab with the defect in the middle of the preset slab according to the preset position, attaching a defect mark to the cut slab, and degrading or changing the defect mark according to the requirement;
J. the steps are carried out on line in real time in the casting process of the casting blank.
2. The method for on-line forecasting of the crack defects in the casting blank according to claim 1, wherein the model computer is a PC (personal computer), an industrial personal computer, a single chip microcomputer or a virtual computer in an L2-level computer.
3. The method for on-line forecasting of the crack defects in the casting blank according to claim 1, wherein the various process and control parameters in the casting process are process parameters related to the heat transfer process of the casting blank, and at least comprise steel grade, tundish molten steel temperature, thickness, drawing speed, width and cooling water flow; the model computer determines the boundary condition of the casting blank heat conduction calculation according to the data, and determines the total heat transferred from the casting blank to the outside in unit time; along with the movement of the physical position of the casting blank, the model computer periodically updates the initial value and the boundary condition of the casting blank heat transfer calculation.
4. The method as claimed in claim 1, wherein the model computer calculates the heat dissipation coefficient of the surface of the cast slab at each time based on the amount of cooling water and the amount of cooling gas, and then calculates the amount of heat dissipated to the outside of the surface of the cast slab per unit time based on the calculated heat dissipation coefficient, thereby obtaining the temperature fields of the inside and the outside of the cast slab based on the physical parameters of the steel type.
5. The method for on-line forecasting of the crack defect in the casting blank according to claim 4, wherein the amount of heat dissipated to the outside of the casting blank during the cooling process is calculated by using the following expression:
φ＝h(Us-Uw)(w/m2)
where phi is the intensity of outward heat dissipation per unit area, UsIs the surface temperature of the cast slab, UwIs the temperature of the cooling water, and h is the heat dissipation coefficient of the casting blank surface.
6. The method for on-line forecasting of the crack defect in the casting blank according to claim 5, wherein the heat dissipation coefficient of the surface of the casting blank is calculated by the following expression:
h＝kwrwara
wherein w is the water flow density and rw is the water volume factor; a is gas density, ra is gas coefficient, and k is constant.
7. The method for on-line forecasting of the crack defect in the casting slab according to claim 4, wherein the water flow density is calculated by calculating the total amount of water sprayed on the upper surface of the casting slab in a certain cooling zone by taking the cooling zone as a unit, and dividing the total amount by the area of the cooling zone to obtain the water flow density; the calculation method of the gas volume density is the same as that of the water flow density.
8. The method for on-line forecasting of the crack defect in the casting blank according to claim 1, wherein the model computer calculates the solidification rate of each position on the casting blank first, and then calculates the solidification thickness according to the solidification rate;
the calculation expression of the solidification rate is as follows:
wherein fs is the solidification rate of the cast slab, TlIs the liquidus temperature, T, of the steelsIs the solidus temperature, T, of the steelcIs the temperature on the center line of the plate blank;
and the model computer calculates the solidification rate of each position on the cross section of the casting blank by using the calculation expression, and then calculates the solidification thickness of each position.
9. The method for on-line prediction of crack defects in a casting slab according to claim 1, wherein the model computer calculates bulging strain, straightening strain and dislocation strain, respectively, based on the temperature field distribution and solidification thickness information of the casting slab obtained by the calculation, superimposes these strains, and calculates the total strain at each slab slice position in units of slab slices.
10. The method for on-line forecasting of the internal crack defect of the casting blank according to claim 9, wherein the bulging strain is calculated by adopting the following expression:
in the formula:
εb(i) the method comprises the following steps Bulging strain, s, of the casting blank solidification interface at the ith rolli: casting blank solidification thickness l corresponding to the ith casting roll positioni: ith roller spacing, δi: amount of bulging deformation.
11. The method for on-line forecasting of the crack defect in the casting blank according to claim 10, wherein the calculation formula of the bulging deformation of the casting blank is as follows:
for a slab, η α is 1; p: the hydrostatic pressure of molten steel borne by the casting rolls; v. ofg: the blank drawing speed; e: the coefficient of elasticity.
12. The method for on-line forecasting of the crack defect in the casting blank according to claim 11, wherein the elastic coefficient is calculated according to the following formula:
wherein, TSTo the setting temperature, TfIs the surface temperature, TMIs an averageAnd (3) temperature.
13. The method for on-line forecasting of the crack defect in the casting blank according to claim 12, wherein the calculation formula of the average temperature is as follows:
wherein, TSTo the setting temperature, TfIs the surface temperature.
14. The method for on-line forecasting of the crack defect in the casting blank according to claim 9, wherein the straightening strain of the casting blank is calculated by the following formula:
in the formula:
si: the thickness of a casting blank solidified shell at the ith straightening roller;
d: the thickness of a casting blank;
Ri: the radius of the outer arc of the casting blank before the ith straightening roll;
Ri+1: casting blank outer arc radius after the ith straightening roll;
εu(i) the method comprises the following steps And straightening strain of the casting blank corresponding to the ith straightening roller.
15. The method for on-line forecasting of the crack defect in the casting blank according to claim 9, wherein the dislocation strain is the strain on the solidification interface of the casting blank caused by the misalignment of the continuous casting pinch rolls, and the calculation formula is as follows:
wherein epsilonm(i)The strain generated on the solidification interface at the ith roller due to roller dislocation; deltamIs the amount of misalignment at the roller; siIs the thickness of the cast slab at the ith roll.
16. The method of on-line prediction of crack defects in a cast slab according to claim 9, wherein the model computer obtains the total strain distribution of the cast slab by:
and (3) taking the position of the casting roll as an index parameter, searching in all slices, finding out the slices with the same position, directly substituting the temperature information and the solidification thickness information of the slices into a strain formula for calculation, and calculating the total strain according to the casting roll after all strain indexes are calculated to obtain the current total strain distribution of the casting blank.
17. The method of on-line prediction of crack defects in a cast slab according to claim 9, wherein the model computer obtains the total strain distribution of the cast slab by:
and taking the position of the casting roll as an index parameter, searching in all the slices, finding out two slices closest to the position of the casting roll, obtaining casting blank temperature and solidification thickness information corresponding to the position of the casting roll by linear interpolation according to the position of the casting roll, the positions of two adjacent slices in the front and back, and the temperature information and the solidification thickness information recorded on the two slices in the front and back, and bringing the casting blank temperature and the solidification thickness information into a strain formula for calculation, and calculating total strain according to the casting roll after all strain indexes are calculated to obtain the current total strain distribution of the casting blank.
18. The method according to claim 9, wherein the method comprises classifying steel types in advance, setting critical strain values for each type of steel, storing the parameters in a database of a model computer prediction model, indexing corresponding critical strain from the database according to the type of poured steel during model computer calculation, sequentially judging the total strain of the casting blank corresponding to each casting roll from the outlet of the casting machine toward the crystallizer by the model computer, judging whether the total strain exceeds the total critical strain, and if the strain exceeds the critical strain value, judging that an internal crack defect occurs, and recording the occurrence position information of the defect by the model computer.
19. The method for on-line forecasting of the internal crack defect of the casting blank according to claim 9, characterized in that the critical strain value range of the casting blank is between 0.5% and 0.8%, the limit strain which the casting blank can bear is related to the steel type, and the specific value is obtained through process tests.
20. The method according to claim 1, wherein when the model computer determines that the crack occurs in the cast slab, the model computer records the specific location of the crack and tracks the duration of the crack to determine the area covered by the crack on the cast slab.
21. The method for on-line forecasting of the crack defect in the casting blank according to claim 1, characterized in that after the model computer completes the calculation, the information of the calculation result is transmitted to a process computer for controlling the cutting of the casting blank through a network, and the casting blank is optimally cut according to the characteristics of the severity degree, the size of the area and the like of the defect, so that the yield of the product is improved.
22. The method for on-line forecasting of the crack defect in the casting blank according to claim 1, wherein the whole casting blank is divided into a series of slices having the same area as the cross section of the casting blank along the casting direction to form the casting blank slice; the heat transfer calculation of the casting blank is carried out on the casting blank slices, and the calculation of a fixed time period is carried out; the model computer can obtain temperature information of any position of the casting blank through interpolation calculation according to the temperature field information of each casting blank slice; the calculation of the casting blank solidification thickness, the temperature field information and the solid phase temperature is also carried out on the casting blank slices.
23. The method of on-line prediction of crack defects in a cast slab according to claim 1, wherein the description of the mathematical model of the heat transfer process of the cast slab includes the calculation of solidification of the continuous cast slab, the boundary conditions of the temperature distribution equation, and the initial conditions for solving the temperature distribution equation.
24. The method for on-line prediction of crack defects in a cast slab according to claim 1, wherein the calculation of solidification of the continuously cast slab is performed from the mold and is completed before the slab exits from the casting machine, and for the slab, only the heat conduction in the thickness direction is considered, and the heat conduction in the casting direction and the width direction of the cast slab is not considered; the liquid phase initial temperature of the molten steel is equal to the tundish temperature; the cooling intensity is kept unchanged in the same cooling section of the continuous casting.
25. The method of on-line prediction of defects of strand internal cracks according to claim 24, wherein the calculation of solidification of the continuous cast slab is described by the following expression:
wherein: x is the distance from the surface of the casting blank; t is casting start time; u (x, t) is the temperature distribution of the section of the casting blank; rho is density; c is specific heat; k is the thermal conductivity.
26. The method of on-line forecasting of the crack defect in the casting blank according to claim 23, wherein the boundary conditions of the temperature distribution equation are as follows:
surface temperature of cast piece U (0, t) is Us，
Wherein, UsIs the surface temperature of the cast piece, h is the heat transfer coefficient, UwCooling water temperature, UextIs the ambient temperature, σ is the Stefan-Boltzmann constant, and ε is the jetness coefficient.
27. The method for on-line forecasting of the internal crack defect of the casting blank according to claim 23, wherein the initial condition for solving the temperature distribution equation is as follows:
assuming that the time T of molten steel injection into the mold is 0, U (x, 0) is TTD；
Initial value of solidification thickness: x is the number ofs|t-0＝0
Initial value of surface temperature: u shapes|x＝0＝TS
Wherein: t isTDThe tundish temperature and TS the solid phase temperature.
28. The method for on-line forecasting of the internal crack defect of the casting blank according to claim 1, wherein the interval period is a time unit of the second level, and the specific value range is between 5 and 10 seconds.
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