A reheating furnace slab moving speed calculation method adaptive to pulsating tapping rhythm

Abstract

The present application relates to a kind of heating furnace slab moving speed calculation method suitable for pulsating tapping rhythm, including multi-period speed calculation: the short-term, medium-term and average moving speed of the present steel billet is calculated;Speed dynamic optimization is predicted: according to the actual production state of heating furnace, the speed value most representing the future moving trend of blank is selected as the steel billet running speed calculation value;Position and residence time prediction: according to the moving speed of steel billet, its residence time in each heating section is predicted;Furnace temperature setting calculation: according to the heating target temperature, the furnace gas temperature setting value of each heating section is corrected;Implementation and control: issue temperature setting value.The present application can predict the moving speed of blank, optimize the calculation process of heating model, improve the calculation accuracy when the moving speed of blank fluctuates greatly, thereby improve production efficiency, save fuel consumption, realize the stable operation of heating model when the tapping rhythm of heating furnace fluctuates, effectively solve the problem that traditional heating model cannot adapt to pulsating tapping rhythm.

Description

Technical Field

[0001] This invention relates to the field of metallurgical industry technology, and in particular to a method for calculating the moving speed of a slab in a heating furnace that adapts to the rhythm of pulsating steel tapping. Background Technology

[0002] In the manufacturing process of sheet and strip steel, the continuous heating furnace is a key piece of equipment used to heat the billets to the required temperature for subsequent shaping and processing. Accurately controlling and predicting the billet's moving speed directly affects the control precision of the heating model. Currently, heating models predict the billet's moving speed using the ratio of the billet's moving distance to time over a certain period, i.e., the average speed V = S / t (V: billet speed; S: billet moving distance; t: a certain time period). The heating model calculates the billet's time in the furnace based on this speed and then sets the furnace temperature and predicts the billet temperature.

[0003] For example, the invention patent with application number CN201611056623 discloses a method for optimizing the heating curve of a two-dimensional walking beam furnace based on time and furnace length. Step S13 is described as "simultaneously calculating the average moving speed of the billet in the furnace in the most recent period based on the moving speed values ​​v(k), v(k-1), v(k-2)...v(kq) of the most recent control cycles, where q is a pre-given value".

[0004] The problem with the existing calculation methods is that they assume the billet's running speed is uniform and stable. However, due to the complexity of product types and specifications, and the chaotic production rhythm, the charging and unloading rhythms frequently and significantly change, sometimes fast and sometimes slow, exhibiting a disordered and pulsating fluctuation. Existing calculation schemes using average speed often fail to accurately calculate and predict the billet's movement speed in the heating furnace. This causes the heating model to be unable to accurately set relevant process parameters, resulting in deviations in heating temperature settings and leading to under- or over-heating of the billet. This not only affects product quality and wastes energy but also easily forces the heating model to exit automatic mode and switch to manual operation, disrupting the continuous stability and control effect of the process. Therefore, there is an urgent need for a precise calculation method that can adapt to large speed fluctuations. Summary of the Invention

[0005] To address the aforementioned problems, the present invention aims to provide a method for calculating the billet moving speed in a heating furnace that adapts to the pulsating tapping rhythm. This method can predict the billet moving speed, optimize the calculation process of the heating model, improve the calculation accuracy when the billet moving speed fluctuates significantly, comprehensively consider the short-term and long-term speeds of billet movement, improve production efficiency, and save fuel consumption. This ensures the stable operation of the heating model when the furnace tapping rhythm fluctuates, effectively solving the problem that traditional heating models cannot adapt to pulsating tapping rhythms.

[0006] The technical solution adopted in this invention is as follows: The present invention proposes a method for calculating the moving speed of a heating furnace slab that adapts to the rhythm of pulsating steel tapping, which specifically includes the following steps: S1. Multi-period velocity calculation: Calculates the current short-term, medium-term, and average moving velocity of the billet; S2. Predicted speed dynamic optimization: Based on the actual production status of the heating furnace, select the speed value that best represents the future movement trend of the billet as the calculated value of the billet running speed; S3. Position and Dwell Time Prediction: Predict the dwell time of the billet in each heating section based on the billet's moving speed; S4. Furnace temperature setting calculation: Correct the furnace gas temperature setting value of each heating section according to the target heating temperature; S5. Execution and Control: Issue the temperature setpoint.

[0007] Furthermore, step S1 includes: setting multiple velocity calculation intervals at different time scales in the steel-firing model, including short-term, medium-term, and multiple velocity calculation time intervals t1, t2, t3...t4 from the time the billet enters the furnace to the current time. n For each time interval t i The distance traveled by the inner billet is calculated using the basic velocity formula v=s / t to obtain the corresponding velocity values ​​v1, v2, v3, ..., v. n The average moving speed specifically refers to the average moving speed of the billet from the moment it enters the furnace until the current moment.

[0008] Furthermore, step S2 includes: based on the actual length of the heating furnace and the actual steel tapping rhythm, calculating v1, v2, v3, ..., v from step S1. n In the process, the value that best represents the future movement trend of the billet is selected as the prediction speed.

[0009] Furthermore, the predicted velocities are selected as v1, v2, v3, ..., v n The maximum, minimum, or median value, or a new value calculated based on each speed value, is used as the predicted speed value of the billet under the pulsating tapping rhythm.

[0010] Furthermore, step S3 includes: inputting the selected predicted speed value from step S2 into the steel firing model of the heating furnace, and using the selected predicted speed value to predict the running position and residence time of the target billet in each heating section in the future, as well as the target value of the billet temperature.

[0011] Furthermore, step S4 includes: based on the prediction results of step S3 and the process setting temperature curve corresponding to the billet type and specification, the steelmaking model will calculate the slab temperature according to the furnace temperature and compare it with the target value of the slab temperature at the predicted position to calculate the furnace temperature setting value required for the current heating section.

[0012] Furthermore, step S5 includes: the steel burning model sends the calculated furnace gas temperature setpoint to the primary combustion control system of the heating furnace, and the primary combustion system adjusts the gas and air flow parameters according to the temperature setpoint so that the actual furnace temperature gradually approaches and stabilizes at the setpoint, ultimately ensuring that the steel billet reaches the target heating temperature after experiencing the predicted residence time.

[0013] Compared with the prior art, the present invention has the following advantages: The core advantage of this invention lies in its significantly improved adaptability and calculation accuracy of the heating model to pulsating steel tapping rhythms: Accurately capture speed dynamics: By calculating multiple speed values ​​such as short-term, medium-term and full-process average speed, the non-uniformity of billet movement and speed change trends (such as acceleration and deceleration) are characterized in multiple dimensions, avoiding the one-sidedness of single average speed calculation.

[0014] Adaptive speed prediction: Combines furnace conditions (furnace length, rhythm) to dynamically select the most suitable predicted speed value (such as selecting a short-term speed to reflect the acceleration trend), making the prediction closer to the actual working conditions.

[0015] Optimized heating control: Based on accurate predicted speed and position / time information, the steel burning model can more accurately set the furnace temperature of each section, effectively preventing under-burning (insufficient temperature) or over-burning (excessive temperature) caused by inaccurate speed prediction.

[0016] Maintaining automatic model operation: This solves the pain point of traditional models being forced to use manual operation when the rhythm is disordered, ensuring the continuity and stability of process control.

[0017] Energy saving, consumption reduction and efficiency improvement: Precise temperature control avoids ineffective heating, reduces gas consumption, and improves product quality and production efficiency. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating a method for calculating the moving speed of a heating furnace slab that adapts to the rhythm of pulsating steel tapping, as proposed in this invention. Detailed Implementation

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] See appendix Figure 1 The present invention proposes a method for calculating the moving speed of a heating furnace slab that adapts to the rhythm of pulsating steel tapping, which specifically includes the following steps: S1. Multi-period velocity calculation: Calculates the current short-term, medium-term, and average moving speed of the billet.

[0021] In the steelmaking model of the heating furnace, multiple velocity calculation intervals with different time scales are set, including three or more velocity calculation time intervals t1, t2, t3, ... t3, including the short-term t1, the medium-term t2, and the time interval t3 from the billet entering the furnace to the current time. n .

[0022] For the distance the billet travels within each time interval ti, the basic speed formula v = s / t is used (where v is the calculated speed and s is the distance traveled in that time interval t). i The distance the inner blank moves, t is the time interval t i The corresponding velocity values ​​v1, v2, v3, ..., v are calculated respectively. n The average moving speed specifically refers to the average moving speed of the billet from the moment it enters the furnace until the current moment.

[0023] S2. Predicted speed dynamic optimization: Based on the actual production status of the heating furnace, select the speed value that best represents the future movement trend of the billet as the calculated value of the billet running speed; Based on the actual length of the heating furnace and the actual steel tapping rhythm, multiple velocity values ​​(v1, v2, v3, ..., v) are calculated from step S1. n In the calculation, the value that best represents the future movement trend of the billet is selected as the prediction speed.

[0024] The optimal strategy is flexible and can select the maximum value (corresponding to the fastest expected pace), the minimum value (corresponding to the slowest expected pace), or an intermediate value, or a new value calculated based on these speed values ​​(such as a weighted average). It can also add a compensation value to the calculated value as the speed prediction value of the billet under the pulsating tapping rhythm.

[0025] S3. Position and Dwell Time Prediction: Predict the dwell time of the billet in each heating section based on the billet's moving speed; The selected predicted speed value in step S2 is input into the steel firing model of the heating furnace. The steel firing model uses the selected predicted speed value to predict the running position and residence time of the target billet in each heating section in the future and the target temperature of the billet (the billet heating curve).

[0026] S4. Furnace temperature setting calculation: Correct the furnace gas temperature setting value of each heating section according to the target heating temperature; Based on the prediction results of step S3, the process setting temperature curves corresponding to the billet type and specifications, and the difference between the billet temperature and the target billet temperature, the furnace temperature setting values ​​required for each heating section are calculated by the steel burning model of the heating furnace.

[0027] S5. Execution and Control: Issue the furnace temperature setpoint; The steel burning model sends the calculated furnace gas temperature setpoint to the primary combustion control system of the heating furnace. The primary combustion system adjusts the gas and air flow parameters according to the temperature setpoint, so that the actual furnace temperature gradually approaches and stabilizes at the setpoint, ultimately ensuring that the steel billet reaches the target heating temperature after experiencing the predicted residence time.

[0028] Traditional methods for calculating furnace in-furnace time and production rhythm rely on regression or time-series analysis to predict the already occurring rhythm in the furnace or rolling mill. However, these methods lack solutions for unstable or nonlinear production rhythms. When production rhythm cannot be predicted, qualitative fuzzy conditions can be quantified into a computable set using membership degrees. Multivariate nonlinear logical reasoning can then be performed based on process rules, followed by defuzzification to output executable predictable values.

[0029] The working principle of this invention is: Fuzzy Time Series Prediction (FTS) (suitable for batch continuous rolling time series prediction).

[0030] The historical multi-step production rhythm time series is divided into fuzzy intervals, a fuzzy time series state transition matrix is ​​constructed, the transition probability from the previous fuzzy state to the next fuzzy state is calculated, and the subsequent N-step production interval is recursively predicted.

[0031] The computer works as follows: Segment the historical time series to generate fuzzy time series F(t) n),F(t n+1)…F(t); Establish the state transition rule: F(t) → F(t+1); The fuzzy prediction value for the next time step is obtained by weighted summation of multiple transfer paths, and then the fuzzy output is defuzzified.

[0032] The present invention will be further illustrated below through specific embodiments: When the steel billets in a slab heating furnace vary greatly in type, specification, and process, and are frequently changed, making it difficult to predict the tapping time and temperature settings, and it is impossible to simultaneously consider the heating temperature of each steel billet in the furnace, the method of this invention can be used to calculate the billet moving speed and set the furnace temperature. The specific implementation process is as follows: Step S1, Multi-time Period Speed ​​Calculation: Divide the historical multi-step production rhythm time series into fuzzy intervals to generate a fuzzy time series. Set three speed values: short-term, medium-term, and average speed, and calculate the specific speed value of a steel billet in the furnace at the current moment. The short-term speed is set as the billet moving speed within t1=15min. The calculated short-term speed is v1=210mm / min. The intermediate speed is set as the billet movement speed within t2=30min, and the short-term speed is calculated to be v2=213mm / min; The average speed is set as the billet movement speed from the moment the billet enters the furnace to the present moment. The calculated average speed is v3 = 159 mm / min.

[0033] Step S2, Predicted Speed ​​Dynamic Optimization: From the above three speed values, it can be seen that the recent billet movement speed (v1, v2) is significantly higher than the average speed throughout the process (v3). The billet movement speed shows a gradually accelerating rhythm. Therefore, in combination with the current accelerated steel tapping rhythm, according to the state transition rule, the short-term speed v1 = 210 mm / min, which best reflects the recent acceleration state, is selected as the predicted speed for the billet's subsequent movement in the furnace.

[0034] Step S3, Position and Dwell Time Prediction: Assuming the billet is currently at the end of the first heating section of the furnace, it still needs to pass through the second heating section and the soaking section before it leaves the furnace. The lengths of the two heating sections are 10m and 11m, respectively. The time it takes for the billet to pass through the two heating sections can be calculated as t(second heating section) = 10000 / 210 = 47.6min and t(soaking section) = 11000 / 210 = 52.4min, respectively, thus outputting the fuzzy prediction value for the next moment.

[0035] Step S4, Furnace Temperature Setting Calculation: Based on the set heating curve of the steel billet of this type and specification, the heating furnace steel burning model calculates the furnace gas temperature setting values ​​of the steel billet in the two heating sections to reach the target temperature, according to the set temperatures of the steel billet leaving the second heating section and the soaking section, and the time in the two heating sections t(second heating section) = 47.6 min and t(soaking section) = 52.4 min.

[0036] Step S5, Execution and Control: The steel burning model sends the calculated furnace gas temperature setpoint to the primary combustion control system of the heating furnace. The primary combustion system adjusts parameters such as gas flow and air flow according to the temperature setpoint, so that the actual furnace temperature gradually approaches and stabilizes at the setpoint, ultimately ensuring that the steel billet reaches the target heating temperature after experiencing the predicted residence time.

[0037] This method enables stable calculation output of the steel-burning model in the heating furnace. Previously, due to the difficulty in predicting the steel-burning rhythm of the model, the heating furnace temperature setting required frequent manual intervention (accounting for about 20%, and even being shut down due to frequent overheating of the model setting value). After calculation using the method of this invention, the automation rate of the steel-burning temperature setting in the heating furnace reaches more than 98%, and there is basically no need for manual intervention.

[0038] All matters not covered in this invention are common knowledge.

[0039] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for calculating the slab moving speed in a heating furnace adapted to a pulsating tapping rhythm, characterized in that, The method includes the following steps: S1. Multi-period velocity calculation: Calculates the current short-term, medium-term, and average moving velocity of the billet; S2. Predicted speed dynamic optimization: Based on the actual production status of the heating furnace, select the speed value that best represents the future movement trend of the billet as the calculated value of the billet running speed; S3. Position and Dwell Time Prediction: Predict the dwell time of the billet in each heating section based on the billet's moving speed; S4. Furnace temperature setting calculation: Correct the furnace gas temperature setting value of each heating section according to the target heating temperature; S5. Execution and Control: Issue the temperature setpoint.

2. The method for calculating the slab moving speed of a heating furnace adapted to the rhythm of pulsating steel tapping, as described in claim 1, is characterized in that: Step S1 includes: in the steelmaking model, setting multiple velocity calculation intervals with different time scales, including short-term, medium-term, and multiple velocity calculation time intervals t1, t2, t3...t4, including short-term, medium-term, and the time interval from billet entering the furnace to the current moment. n For each time interval t i The distance traveled by the inner billet is calculated using the basic velocity formula v=s / t to obtain the corresponding velocity values ​​v1, v2, v3, ..., v. n The average moving speed specifically refers to the average moving speed of the billet from the moment it enters the furnace until the current moment.

3. The method for calculating the slab moving speed of a heating furnace adapted to the rhythm of pulsating steel tapping, as described in claim 1, is characterized in that: Step S2 includes: based on the actual length of the heating furnace and the actual steel tapping rhythm, calculating v1, v2, v3, ..., v from step S1. n In the process, the value that best represents the future movement trend of the billet is selected as the prediction speed.

4. The method for calculating the moving speed of a heating furnace slab adapted to the rhythm of pulsating steel tapping, as described in claim 3, is characterized in that: The predicted velocities are selected as v1, v2, v3, ..., v n The maximum, minimum, or median value, or a new value calculated based on each speed value, is used as the predicted speed value of the billet under the pulsating tapping rhythm.

5. The method for calculating the slab moving speed of a heating furnace adapted to the rhythm of pulsating steel tapping, as described in claim 1, is characterized in that: Step S3 includes: inputting the selected predicted speed value from step S2 into the steel firing model of the heating furnace, and using the selected predicted speed value to predict the running position and residence time of the target billet in each heating section in the future, as well as the target value of the billet temperature.

6. The method for calculating the slab moving speed of a heating furnace adapted to the rhythm of pulsating steel tapping, as described in claim 1, is characterized in that: Step S4 includes: based on the prediction results of step S3 and the process setting temperature curve corresponding to the billet type and specifications, the steel burning model will calculate the slab temperature according to the furnace temperature and compare it with the target value of the slab temperature at the predicted position to calculate the furnace temperature setting value required for the current heating section.

7. The method for calculating the moving speed of a heating furnace slab adapted to the rhythm of pulsating steel tapping, as described in claim 1, is characterized in that: Step S5 includes: the steel burning model sends the calculated furnace gas temperature setpoint to the primary combustion control system of the heating furnace. The primary combustion system adjusts the gas and air flow parameters according to the temperature setpoint, so that the actual furnace temperature gradually approaches and stabilizes at the setpoint, and finally ensures that the steel billet reaches the target heating temperature after experiencing the predicted residence time.

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