A rolling method to improve the performance consistency of direct-rolled steel bars

Abstract

This invention provides a rolling method to improve the performance consistency of directly rolled steel bars, belonging to the field of metallurgical technology. The method includes the following steps: obtaining a temperature distribution model predicting the billet temperature change over time based on measured temperature data of the billet during natural cooling; real-time acquisition of time data from the completion of shearing to the entry into water cooling; calculating and predicting the temperature distribution along the length of the billet during water cooling using the temperature distribution model based on the time data; and dynamically adjusting the water cooling intensity using an automated temperature control system based on the predicted temperature distribution, implementing differentiated cooling for different parts of the billet along its length to ensure that the surface temperature of the rolled piece after water cooling and complete reheating is consistent along its length. This invention, through accurate prediction of billet temperature and dynamic adjustment of cooling, fundamentally eliminates performance fluctuations caused by temperature differences between the beginning and end of the rolling process.

Description

Technical Field

[0001] This invention relates to the field of metallurgical technology, and specifically to a rolling method for improving the performance consistency of steel bar direct-rolled products. Background Technology

[0002] In today's fiercely competitive steel market, improving product quality and reducing production costs are crucial for a company's survival and development. As a vital component of the steel industry, steel bar production widely adopts direct rolling technology to respond to the national call for low-carbon and energy-saving cost reduction. Direct rolling, where continuously cast billets are rolled directly without reheating in a traditional furnace, offers significant advantages over traditional processes in terms of energy conservation and reduced oxidation loss.

[0003] However, the direct rolling process itself has an inherent technical bottleneck. During continuous casting and conveying, the head and tail of the steel billet experience different exposure times to air, resulting in a natural cooling time difference. For example, for a 12-meter-long steel billet, the cooling time difference between the head and tail can be several minutes. This leads to a significant temperature gradient along the length of the billet when it enters the first rolling mill, typically manifesting as a higher temperature at the head and a lower temperature at the tail.

[0004] The controlled rolling and cooling equipment and technologies used in existing rebar production lines are mostly designed for steel billets that have been uniformly heated in a furnace. These traditional controlled cooling systems typically use a fixed set of unchanging cooling parameters (such as water pressure and flow rate for water cooling) to process the entire billet. When this fixed cooling mode is applied to directly rolled billets with temperature differences between the beginning and end, it inevitably leads to uneven cooling: the hotter beginning portion of the billet may not be cooled sufficiently, while the cooler end portion may be over-cooled. This temperature inhomogeneity after cooling directly results in significant fluctuations in the mechanical properties (especially yield strength and tensile strength) of the final rebar product along its length. For example, for HRB400E grade rebar, using conventional direct rolling technology, the yield strength fluctuation range can reach ±30MPa, seriously affecting the stability of product quality and high-end applications.

[0005] Therefore, how to economically and effectively eliminate or compensate for the temperature difference between the head and tail of the billet in the direct rolling process, thereby improving the uniformity and stability of the mechanical properties of the final steel reinforcement product, is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] This invention addresses the technical problem of large fluctuations in the mechanical properties of finished steel products caused by temperature differences between the beginning and end of the billet in existing direct rolling processes, and provides a rolling method to improve the consistency of the properties of directly rolled steel bars.

[0007] The technical method of the present invention is as follows: A rolling method for improving the performance consistency of directly rolled steel bars, the method comprising the following steps: S1. Based on the measured temperature data of the billet during the natural cooling process, a temperature distribution model is obtained to predict the change of billet temperature over time. S2. Real-time acquisition of time data from the completion of shearing to the entry of the billet into water cooling; S3. Based on the time data, calculate and predict the temperature distribution along the length of the billet when it enters the water cooling process using a temperature distribution model. S4. Based on the predicted temperature distribution, the water cooling intensity is dynamically adjusted through an automated temperature control system to implement differentiated cooling for different parts of the billet along its length, so that the surface temperature of the rolled piece along its length tends to be uniform after water cooling and complete reheating.

[0008] Optionally, in step S1, the temperature distribution model is determined by regression equation (1): (1) Where T is the predicted billet temperature; t is the cooling time; T env A is the ambient temperature; RH is the ambient humidity; A is the cross-sectional area of ​​the steel billet; V is the volume of the steel billet; T initial τ is the initial measured temperature of the steel billet; τ is the cooling time constant. to These are the coefficients determined through regression analysis. The coefficients of the regression equation are: =712.45, =87.23, =63.78, =0.534, =15.67, =4.91, =19.32, =145.21, =0.748, =0.401.

[0009] Optionally, in step S3, when predicting the temperature distribution of the billet when it enters the water cooling process, the temperature rise or drop during the rolling process is also compensated based on the actual elongation coefficient of the billet.

[0010] Optionally, the method further includes: setting up a high-precision temperature measuring device after water cooling and at the point where the rolled piece has fully warmed up, monitoring the surface temperature of the rolled piece in real time, and using the measured temperature as a feedback signal to automatically correct the automated temperature control system or the temperature distribution model.

[0011] Optionally, the method further includes: setting a mechanical performance import interface in the automated temperature control system, using the measured mechanical performance data of the final product as feedback information to further correct the control logic of the automated temperature control system.

[0012] Optionally, the automated temperature control system is equipped with a controller to adjust the control valve, thereby regulating the water penetration intensity.

[0013] Optionally, after step S4, the surface temperature of the rolled piece after complete reheating is controlled within ±10°C of the target temperature.

[0014] Optionally, the rolled piece is an HRB400E steel bar, and after being rolled by the method, its yield strength fluctuation range is controlled within ±15MPa of the target yield strength.

[0015] Optionally, the temperature range of the rolled piece before entering the water cooling is 880℃~970℃, and the surface temperature range of the rolled piece after water cooling and complete rewarming is 800℃~830℃.

[0016] The beneficial effects of this invention are: I. The method of this invention significantly improves product performance consistency: This invention, through precise prediction of billet temperature and dynamic adjustment of cooling, fundamentally eliminates performance fluctuations caused by temperature differences between the beginning and end of the process. Experimental data shows that the yield strength fluctuation range of HRB400E steel bars produced using the method of this invention is significantly reduced from ±30MPa in conventional processes to ±15MPa, resulting in a substantial improvement in product quality stability and uniformity.

[0017] II. High-Precision Control Achieved by the Method of this Invention: This invention not only achieves model-based predictive control, but also constructs an intelligent control system by introducing measured temperature feedback after water penetration and final mechanical performance feedback. This system possesses adaptive correction capabilities, enabling it to cope with environmental changes and operating condition fluctuations, ensuring continuous, stable, and high-quality production.

[0018] Third, the process applicability of the present invention is strong: the method proposed in this invention does not require large-scale modification of the main equipment of the rolling line. It is mainly achieved by establishing a mathematical model and upgrading the automated control system. It has the advantages of low investment, quick results and easy promotion and application on existing direct rolling production lines. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the rolling method of the present invention for improving the performance consistency of steel bar direct rolling products. Detailed Implementation

[0020] The technical solution of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] This invention provides a rolling method for improving the performance consistency of directly rolled steel bars, such as... Figure 1 As shown, the method includes the following steps: S1. Based on the measured temperature data of the billet during the natural cooling process, a temperature distribution model is obtained to predict the change of billet temperature over time.

[0022] In this embodiment, a large number of temperature tracking measurements were performed on a steel billet of a specific size (e.g., 165mm × 165mm). Initial temperature (T) initial The temperature is measured by a fixed temperature measuring device (such as an infrared thermometer) installed at the billet shearing position. After the billet is sheared, a handheld high-precision thermometer is used to track and measure the surface temperature of the billet at different time points (t) on the conveyor roller, while recording the ambient temperature (Tenv) and ambient humidity (RH) at the same time.

[0023] In this embodiment, the temperature distribution model is determined by a regression equation: Where T is the predicted billet temperature; t is the cooling time; T env A is the ambient temperature; RH is the ambient humidity; A is the cross-sectional area of ​​the steel billet; V is the volume of the steel billet; T initial τ is the initial measured temperature of the steel billet; τ is the cooling time constant. to These are the coefficients determined through regression analysis.

[0024] The regression equation of this invention is designed based on the formulas for radiative heat dissipation (Stefan-Boltzmann law), convective heat dissipation (Newton's cooling law), and heat conduction (Fourier's law).

[0025] In this embodiment, multiple sets (greater than or equal to 20 sets) of training samples are collected from the continuous casting production line. The samples include cooling time t, initial temperature T0, and ambient temperature T. e Ambient humidity (RH) and corresponding actual measured temperature (T).

[0026] Based on the above regression equation form, solve... to This includes the following steps: (1) Construct the design matrix X and response vector y: Construct the design matrix X (200×10): Among them, t 1-200 T represents the cooling time for each of the 200 samples. env1-200 The ambient temperature and humidity (RH) for each of the 200 samples are given. 1-200 T1-200 represents the relative humidity of the environment for each of the 200 samples, T1-200 represents the measured temperature of the steel billet for each of the 200 samples, A represents the cross-sectional area of ​​the steel billet, and V represents the volume of the steel billet.

[0027] Response vector y (200×1): Among them, T 1-200 The actual measured temperature for 200 samples.

[0028] (2) Solving for model coefficients The least squares method is used to determine the regression coefficient vector β = [ by solving the normal equation]. , , ..., ]ᵀ: In the calculation, if the matrix If it approaches singularity, the pseudo-inverse method can be used. To ensure the stability and robustness of the solution, the following steps are taken.

[0029] (3) Model validation and application Substituting the obtained coefficients β into the regression equation yields the final temperature prediction model. The model's goodness of fit is tested by calculating the coefficient of determination (R²), adjusted R², and root mean square error (RMSE). Residual analysis is also performed to verify the rationality of the model's assumptions. Finally, the model's prediction accuracy is validated using independent test datasets (e.g., calculating the mean absolute error and mean relative error). Based on 200 sets of sample data, for example, Table 1 lists 20 data points, construct a 200×10 design matrix X and a 200×1 response vector y. Use the NumPy library in Python to perform matrix operations and solve the normal equations. .

[0030] Table 1 The regression coefficient vector β obtained by solving is: In this embodiment, the coefficients of the regression equation are: =712.45, =87.23, =63.78, =0.534, =15.67, =4.91, =19.32, =145.21, =0.748, =0.401.

[0031] S2. Real-time acquisition of time data from the completion of shearing to the entry of the billet into water cooling.

[0032] In this embodiment, the time data refers to the time from the completion of shearing to the start of the time the billet enters the first rolling mill.

[0033] S3. Based on the time data, calculate and predict the temperature distribution along the length of the billet when it enters the water cooling process using a temperature distribution model.

[0034] In this embodiment, when predicting the temperature distribution of the billet when it enters the water cooling process, the temperature rise or drop during the rolling process is also compensated based on the actual elongation coefficient of the billet.

[0035] S4. Based on the predicted temperature distribution, the water cooling intensity is dynamically adjusted through an automated temperature control system to implement differentiated cooling for different parts of the billet along its length, so that the surface temperature of the rolled piece along its length tends to be uniform after water cooling and complete reheating.

[0036] In this embodiment, the automated temperature control system includes a controller, a temperature control unit, and a temperature detection unit.

[0037] In this embodiment, the method further includes: setting up a high-precision temperature measuring device after water cooling and at the position where the rolled piece has fully recovered its temperature, monitoring the surface temperature of the rolled piece in real time, and using the measured temperature as a feedback signal to automatically correct the automated temperature control system or the temperature distribution model.

[0038] In this embodiment, the method further includes: setting a mechanical performance import interface for the automated temperature control system, using the measured mechanical performance data of the final product as feedback information to further correct the control logic of the automated temperature control system.

[0039] In this embodiment, the automated temperature control system uses a controller to adjust the control valve, thereby regulating the water penetration intensity.

[0040] In this embodiment, after step S4, the surface temperature of the rolled piece after complete reheating is controlled within ±10°C of the target temperature.

[0041] In this embodiment, the rolled piece is an HRB400E steel bar. After being rolled by the method described above, its yield strength fluctuation range is controlled within ±15MPa of the target yield strength.

[0042] In this embodiment, the temperature range of the rolled piece before entering the water cooling is 880℃~970℃, and the surface temperature range of the rolled piece after water cooling and complete rewarming is 800℃~830℃.

[0043] The present invention will be described in detail below through embodiments and experimental examples. However, these are merely examples and do not limit the present invention in any way.

[0044] Example 1 Production conditions: Production of HRB400E steel bars with a specification of Φ25mm. The billet length is 12m, the cross-section is 165mm×165mm, the continuous casting speed is 3.6m / min, and the initial temperature of the billet during shearing is 1000℃.

[0045] Process: The interval between the first and second shearing of a steel billet is 12 / 3.6 = 3.33 minutes, which is the maximum cooling time difference between the head and tail of the billet. After a billet is sheared, the on-site information acquisition equipment measures that it takes 2.5 minutes to reach the first rolling mill. The automated temperature control system immediately starts, and based on the established temperature distribution model, predicts the actual temperature distribution of the billet when it begins rolling. During the rolling process, the system predicts that the temperature range before entering the water tank is 890℃ (tail) to 970℃ (head). Based on this, the system dynamically adjusts the water penetration intensity, providing strong cooling for the billet head and weak cooling for the billet tail.

[0046] Results: After dynamic temperature control, the surface temperature of the rolled piece at the reheating position was stabilized between 810℃ and 830℃, with a fluctuation range of less than ±10℃. Mechanical property tests were conducted on samples taken from the head, middle, and tail positions of this batch of material. The measured yield strength ranged from 430MPa to 440MPa, with a fluctuation range controlled within ±5MPa, which is far superior to conventional processes.

[0047] Example 2 Production conditions: Production of HRB400E steel bars with a specification of Φ18mm. The billet length is 12m, the cross-section is 165mm×165mm, the continuous casting speed is 3.2m / min, and the initial temperature of the billet during shearing is 980℃.

[0048] Process: The maximum cooling time difference between the beginning and end of the billet is 12 / 3.2 = 3.75 minutes. A certain billet takes 3 minutes from shearing to rolling. The system also performs temperature prediction and dynamic cooling control, predicting its temperature range before entering the water tank to be 880℃~960℃.

[0049] Results: After treatment using the method of this invention, the surface temperature of the rolled piece was stabilized between 800℃ and 820℃ at the reheating point. Sampling and testing of the finished product showed that its measured yield strength ranged from 435MPa to 445MPa, with fluctuations also controlled within a very small range, indicating extremely high product performance consistency.

[0050] Comparison of effects: (1) In terms of quality improvement (taking HRB400E as an example, the yield strength internal control requirement is ≥420MPa): Using conventional direct rolling production technology, the yield strength fluctuation range is 450MPa (design target yield strength) ±30MPa. Using the method shown in this patent, the yield strength fluctuation range is 435 MPa (design target yield strength) ± 15 MPa. The yield fluctuation range of the finished product was reduced from ±30MPa to ±15MPa, resulting in a significant improvement in quality.

[0051] (2) Cost reduction: The conventional direct rolling production process is adopted, and the design target value of yield strength is 450MPa. Using the method shown in this patent, the target design value for yield strength is 435 MPa. The target yield strength was reduced by 15 MPa, based on alloying principles and practical experience. Benefit per ton of steel = Cost savings from a 15 MPa reduction in yield strength ≈ 10 yuan / ton. Based on the above, By adopting the results of this invention, the consistency of steel bar performance is significantly improved, directly generating a benefit of approximately 10 yuan per ton.

[0052] Various embodiments of the present invention may exist in the form of a range; it should be understood that the description in the form of a range is merely for convenience and brevity and should not be construed as a hard limitation on the scope of the invention; therefore, it should be considered that the range description has specifically disclosed all possible subranges and single numerical values ​​within that range. For example, it should be considered that the range description from 1 to 6 has specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6, etc., and single numbers within the range, such as 1, 2, 3, 4, 5, and 6, regardless of the range. Furthermore, whenever a numerical range is referred to herein, it means including any referenced number (fraction or integer) within the range referred to.

[0053] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A rolling method for improving the performance consistency of directly rolled steel bars, characterized in that, The method includes the following steps: S1. Based on the measured temperature data of the billet during the natural cooling process, a temperature distribution model is obtained to predict the change of billet temperature over time. S2. Real-time acquisition of time data from the completion of shearing to the entry of the steel billet into water cooling; S3. Based on the time data, calculate and predict the temperature distribution along the length of the billet when it enters the water cooling process using a temperature distribution model. S4. Based on the predicted temperature distribution, the water cooling intensity is dynamically adjusted through an automated temperature control system to implement differentiated cooling for different parts of the billet along its length, so that the surface temperature of the rolled piece along its length tends to be uniform after water cooling and complete reheating. In step S1, the temperature distribution model is determined by regression equation (1): （1） Where T is the predicted billet temperature; t is the cooling time; T env A is the ambient temperature; RH is the ambient humidity; A is the cross-sectional area of ​​the steel billet; V is the volume of the steel billet; T initial τ is the initial measured temperature of the steel billet; τ is the cooling time constant. to The coefficients were determined through regression analysis; the coefficients of the regression equation are as follows: =712.45, =87.23, =63.78, =0.534, =15.67, =4.91, =19.32, =145.21, =0.748, =0.401; In step S3, when predicting the temperature distribution of the billet when it enters the water cooling process, the temperature rise or drop during the rolling process is also compensated based on the actual elongation coefficient of the billet. The method further includes: setting up a high-precision temperature measuring device after water cooling and at the position where the rolled piece has fully recovered its temperature, monitoring the surface temperature of the rolled piece in real time, and using the measured temperature as a feedback signal to automatically correct the automated temperature control system or the temperature distribution model. The temperature range of the rolled piece before entering the water cooling process is 880℃~970℃, and the surface temperature range of the rolled piece after water cooling and complete rewarming is 800℃~830℃.

2. The method according to claim 1, characterized in that, The method further includes: The automated temperature control system is equipped with a mechanical performance import interface, which uses the measured mechanical performance data of the final product as feedback information to further correct the control logic of the automated temperature control system.

3. The method according to any one of claims 1-2, characterized in that, The automated temperature control system uses a controller to adjust the control valve, thereby regulating the water penetration intensity.

4. The method according to claim 1, characterized in that, After step S4, the surface temperature of the rolled piece after complete reheating is controlled within ±10℃ of the target temperature.

5. The method according to claim 1, characterized in that, The rolled piece is an HRB400E steel bar. After being rolled by the method described above, its yield strength fluctuation range is controlled within ±15MPa of the target yield strength.

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