A method for efficient cutting of a continuous casting beam blank

Abstract

This invention relates to a method for efficient cutting of continuously cast irregular-shaped billets, belonging to the technical field of continuously cast irregular-shaped billet production methods. The technical solution of this invention is as follows: Real-time data during continuous casting production is collected; the casting speed is accumulated over time to calculate the cumulative length of the billet in real time, and the corresponding time when the billet is in the liquid state is calculated; based on the corresponding time when the billet is in the liquid state and the process parameters, the heat flux density of each billet is determined; the correspondence between the time of changing the tundish / intermediate ladle and the cutting time of the affected billet is found to identify the affected billet; the state of the molten steel and the distribution of defects are monitored in real time, and the cutting scheme is dynamically calculated in conjunction with process constraints. The beneficial effects of this invention are: it can simulate data for all billets in continuous casting, optimize the cutting of areas with dense defects, record all key time nodes, generate billet information quality reports, and perform detailed quality control of the billets.

Description

Technical Field

[0001] This invention relates to a method for efficient cutting of continuously cast irregular-shaped billets, belonging to the technical field of continuous casting irregular-shaped billet production methods. Background Technology

[0002] In the production of special-shaped billets through continuous casting, the solidification behavior of molten steel from liquid to solid directly affects the quality of the final billet (such as surface cracks, internal segregation, shrinkage cavities, and other defects). Due to the complex cross-sectional shapes of special-shaped billets (such as I-beams and H-beams), their solidification process is more challenging than that of ordinary slabs or square billets—problems such as uneven cooling and stress concentration are more prominent. Therefore, by analyzing liquid production parameters (such as tundish temperature, casting speed, crystallizer heat flux, and secondary cooling intensity), combined with solidification models and quality inspection data, the correlation between liquid process and solid billet quality can be established, thereby optimizing process settings, reducing defects, and improving the pass rate and performance of special-shaped billets. This research is of great significance for improving the production efficiency and quality control of special continuously cast billets.

[0003] In continuous casting production, billet cutting is a critical step affecting yield. Factors such as nozzle changes, tundish changes, molten steel level fluctuations, and casting speed variations can cause defects like segregation, cracks, and inclusions during the solidification process, leading to substandard billet quality in certain areas. Traditional cutting methods, using fixed lengths (e.g., 6 meters, 9 meters, 12 meters), cannot dynamically adapt to defect distribution, resulting in the removal of some qualified billets or incomplete removal of defective billets, impacting yield and product quality.

[0004] Patent application number 202110541570.1 discloses "A method for identifying and optimizing the cutting of continuously cast unsteady billets in a single step." This method tracks the molten steel from the tundish to the cutting machine, tracks the cutting position by heat number, and divides the cutting length according to a fixed length to calculate the optimal cutting scheme. However, this method can only optimize cutting for simple issues such as changing the nozzle, replacing the tundish, and adjusting the width. It mainly relies on a uniform-length cutting model, which still results in oversized cuts and waste. Summary of the Invention

[0005] The purpose of this invention is to provide a method for efficient cutting of continuously cast irregular-shaped billets. By statistically analyzing the dynamic changes of key process parameters, a quantitative correlation model between these parameters and the quality defects of solid billets is established. The optimal cutting method is calculated in real time. Data simulation can be performed on all billets in continuous casting, and cutting optimization can be performed on areas with dense defects. All key time nodes are recorded, and billet information quality reports are generated for detailed quality control of the billets. This effectively solves the aforementioned problems existing in the background technology.

[0006] The technical solution of this invention is: a method for efficient cutting of continuously cast irregular-shaped billets, comprising the following steps:

[0007] (1) Data preparation: collect real-time data during continuous casting production, including real-time values ​​of key process parameters such as actual casting speed, actual liquid level and secondary cooling water flow rate, in order to calculate the parameter changes during the liquid-solid conversion process.

[0008] (2) Calculate the actual time period corresponding to the billet, accumulate the casting speed in the time direction, calculate the cumulative length of the billet in real time, and back-calculate the actual time corresponding to the billet when it is in the liquid state;

[0009] (3) Heat flux density calculation: Based on the corresponding time and process parameters when the billet is in the liquid state, the heat flux density of each billet is calculated;

[0010] (4) When changing the nozzle / tundish, find the correspondence between the nozzle / tundish changing operation time and the fire cutting time of the affected billet to determine the affected billet;

[0011] (5) Calculate the billet cutting, monitor the state of molten steel and the distribution of defects in real time, and dynamically calculate the cutting scheme in combination with process constraints.

[0012] Step (1) includes the following steps:

[0013] The set value of the casting speed and the actual value of the casting speed of the continuous casting machine are collected in real time as the basic data for modeling;

[0014] Real-time crystallizer liquid level information is collected as the basic data for modeling, and the real-time value of liquid level fluctuation is calculated by difference.

[0015]

[0016] in This represents the liquid level fluctuation value. This is the actual value of the liquid level in the crystallizer; Set the liquid level setting for the crystallizer;

[0017] Real-time acquisition of key data on real-time cooling water flow in the secondary cooling zone.

[0018] In step (2), after the casting speed increases, the length of the billet passing through the casting machine inlet is accumulated in real time, and then the corresponding billet cutting information is generated according to the real-time signal of the fire cutter clamp.

[0019]

[0020] in:

[0021] This refers to the total cumulative length of the billet passing through the casting machine inlet; The lifting time is the time required for the speed to increase. This refers to the time for the pull speed to return to zero. For instantaneous acceleration; This is the interval time (1 second in this case);

[0022] When the cutting occurs, calculate the first... The cumulative length information of the ingot casting is calculated as follows:

[0023]

[0024] in: For the first The cumulative length of the billet in the block; The lifting time is the time required for the speed to increase. The current time; For instantaneous acceleration; This is the interval time, which is 1 second here; For the first Length of the ingot casting;

[0025] Based on the change in the remaining length in the fire-cutting machine Retrospectively calculate the entry time of each casting billet. , billet casting end time and duration of passage The backtracking method is as follows:

[0026] 1) Selecting the billet entry time

[0027] a) If this is the first cast billet, then That is, the lifting speed and time;

[0028] b) If it is not the first cast billet, then That is, the end time of the previous casting billet;

[0029] 2) Duration of billet back-pushing

[0030] a) Traversing the first Cumulative length of ingot casting at various time points ;

[0031] b) When When the changed length is less than or equal to the cumulative length, the time at which this occurs is the billet casting end time. ;

[0032] c) Calculate the billet transit time

[0033]

[0034] Obtain the entry time from the billet End time of billet casting Information on liquid level fluctuations and key processes of secondary cooling water.

[0035] In step (3), the heat flux density is calculated as follows:

[0036]

[0037] in: Heat flux density; This refers to the specific heat capacity of the cooling water. This refers to the cooling water flow rate; For changes in cooling water temperature; This refers to the outlet temperature of the cooling water. This refers to the inlet temperature of the cooling water. The total contact area, For the width area, For narrow face area;

[0038] The cooling water throughput is calculated cumulatively from the cooling water flow rate, as follows:

[0039]

[0040] in: This refers to the cooling water flow rate; This refers to the start time of billet casting; This refers to the end time of billet casting; This refers to the instantaneous cooling water flow rate; This is the interval time, which is 1 second here.

[0041] Step (5) includes the following steps:

[0042] 1) Defect data acquisition: Real-time monitoring of crystallizer status, casting speed, and defect points or sections during nozzle / tundish replacement to obtain the defect location of the billet. Defect data is then assessed and quantified. For any position x along the length of the billet, a quality confidence level is defined.

[0043]

[0044] in: The process fluctuation index is a statistical analysis of abnormal conditions in parameters such as casting speed, liquid level, and secondary cooling flow rate over a corresponding time period. For the corresponding abnormal segment of the billet parameters, then ;

[0045] The heat flux index is used to inversely deduce the solidification front stability from the integral of the heat flux density. For the corresponding segregation / crack risk impact section, then ;

[0046] Mark the event disturbance if For the section affected by replacing the water inlet / intermediate refrigerant, then ;

[0047] This provides a data foundation for calculating the overall defects of the billet and for subsequent sliding window calculations.

[0048] For defective data, the original data undergoes secondary processing using a defect filling mechanism:

[0049] a) When the defect interval does not reach the minimum cutting length, the defects are considered to be connected;

[0050] b) When the defect interval reaches the minimum cutting length or exceeds the maximum cutting length, no operation is performed on the defect data;

[0051] 2) Sliding window constrained dynamic programming: Based on the defect data, a dynamic programming mechanism is designed as follows:

[0052] a) Discrete segmentation: The 30-meter billet is discretized into several segments, each 0.5 meters long, and the defect locations are marked.

[0053] b) Define state variables: Traverse upwards from the cutting direction to record the current cutting start point and the remaining length to be cut;

[0054] c) Define the objective function: maximize the effective billet length and minimize the segment containing billet defects;

[0055] d) Constraints: The length of each segment is within the process range and avoids areas with dense defects; the minimum remaining normal segment of the cast billet;

[0056] 3) Optimize the solution by using dynamic programming recursive calculation to derive the optimal cutting point from the end of the billet, ensuring that each cut is within the compliant length range and that the impact of defects is minimized;

[0057] a) Calculation method for the defect front end, i.e., the first billet to be included:

[0058] When any defect is detected, wait for the last billet to be cut, then divide the remaining normal billets into the smallest cutting units that meet the conditions, while ensuring that billet waste is minimized.

[0059] The calculation method is as follows:

[0060]

[0061] in: This represents the total length of the normal cast billet to be calculated. This indicates the cutting length of each segment of the cast billet. Represents the number of segments. Remaining length , Minimum cutting length;

[0062] To ensure the cutting length of each section of the cast billet. exist Between meters, length The remaining billet length must fluctuate within a reasonable range according to the planned length. The optimal cutting method is to make it as small as possible;

[0063] Traversing the fixed length within a reasonable range Calculate the length of the billet to meet the requirements, and follow the... The remaining length of the cast billet after cutting is [length]. Minimum, record minimum The following fixed length This completes the cutting of subsequent normal segments;

[0064] b) Calculation method for defective middle section:

[0065] When the head of the defective billet enters the cutting position, skip all defective billets and cut the defective section as little as possible within a reasonable billet length range; if the defect interval is within... Between meters, the internal normal casting billet is cut in the same way as the defective front end;

[0066] Based on the filled defect segment data, defect segment cutting calculations are performed, satisfying the following formula:

[0067] First calculate the minimum number of cuts required. part, For positive integers:

[0068]

[0069] in: This represents the total length of the abnormal billet to be calculated. Represents the number of segments. Remaining length , This is the maximum cutting length;

[0070] Based on the calculated number of segments Calculate the fixed length when cutting uniformly. :

[0071]

[0072] in: This represents the total length of the abnormal billet to be calculated. Represents the number of segments. This is the adjusted fixed length;

[0073] If the defect interval is greater than If the defect segment is cut off, the calculation of a new defect segment begins.

[0074] c) Calculation method for the defective end-stage, i.e., the later-entering billet:

[0075] When the continuous defects end, wait for the defect end position to leave the rolling mill, cut at the end position, calculate the subsequent normal cutting position and repeat the normal cutting process;

[0076] 4) Real-time adjustment, online updating of the cutting plan, and sending instructions to the flame cutting machine for execution, dynamically adjusting the fixed length;

[0077] 5) Calculation process: Real-time adjustment of billet cutting; determination of whether the current cutting scheme matches the planned scheme; if defects are concentrated, adjustment to a more reasonable cutting scheme:

[0078] After casting begins, the current drawing length is accumulated in real time, the process parameters during the drawing process are monitored, and defect information is recorded at any time. The drawn billet is dynamically planned in real time to obtain the optimal billet cutting scheme. Combined with the current fixed length of the flame cutter, it is determined whether the optimal cutting can be achieved. If it can, the cutting is carried out normally. If not, the fixed length of the flame cutter needs to be adjusted according to the optimal scheme, and the billet with dense defects is removed first.

[0079] The beneficial effects of this invention are: by statistically analyzing the dynamic change patterns of key process parameters, a quantitative correlation model between these parameters and solid billet quality defects is established, the optimal cutting method is calculated in real time, data simulation can be performed on all billets in continuous casting, cutting optimization can be performed on areas with dense defects, all key time nodes are recorded, billet information quality reports are generated, and detailed quality control of the billets is achieved. Attached Figure Description

[0080] Figure 1 This is a flowchart of the method of the present invention;

[0081] Figure 2 This is a schematic diagram of the continuous casting process of the present invention;

[0082] Figure 3 This is a diagram of the billet state during the replacement of the sprue / tundish in this invention, where red indicates defective sections;

[0083] Figure 4 This is a schematic diagram illustrating the meaning of the defect icons in this invention;

[0084] Figure 5 This is a curve showing the defect in the pulling speed of this invention;

[0085] Figure 6 This is a curve diagram of liquid level fluctuation defects according to the present invention;

[0086] Figure 7 This is a defect curve diagram of the water inlet / intermediate refrigerant replacement invention;

[0087] Figure 8 This is a comprehensive evaluation defect curve of the billet of this invention;

[0088] Figure 9 This is a schematic diagram of defect filling in this invention;

[0089] Figure 10 This is a graph showing the cumulative length curve and the remaining length curve of Embodiment 1 of the present invention;

[0090] Figure 11 This is a graph showing the abnormal pulling speed in Embodiment 1 of the present invention;

[0091] Figure 12 This is a diagram showing the processing of abnormal pulling speed curves in Embodiment 1 of the present invention;

[0092] Figure 13 This is a graph showing the liquid level fluctuation in Embodiment 1 of the present invention;

[0093] Figure 14 This is a processed graph of the liquid level fluctuation curve from Embodiment 1 of the present invention;

[0094] Figure 15 This is the cold water abnormality curve diagram of Embodiment 1 of the present invention;

[0095] Figure 16 This is a diagram showing the abnormal cooling water curve processing in Embodiment 1 of the present invention;

[0096] Figure 17 This is a comprehensive defect curve diagram of Embodiment 1 of the present invention;

[0097] Figure 18 This is a diagram showing the actual cutting position in Embodiment 1 of the present invention;

[0098] Figure 19 This is a graph showing the abnormal pulling speed in Embodiment 2 of the present invention;

[0099] Figure 20 This is a diagram showing the abnormal pulling speed curve processing in Embodiment 2 of the present invention;

[0100] Figure 21 This is a graph showing the liquid level fluctuation in Embodiment 2 of the present invention;

[0101] Figure 22 This is a processed graph of the liquid level fluctuation curve from Embodiment 2 of the present invention;

[0102] Figure 23 This is a comprehensive defect curve diagram of Embodiment 2 of the present invention;

[0103] Figure 24 This is a diagram showing the actual cutting position in Embodiment 2 of the present invention;

[0104] In the diagram: Stream 1, Stream 2, Stream 3, Stream 4, Stream 5, Ladle 6, Tundish 7. Detailed Implementation

[0105] To make the purpose, technical solutions, and advantages of the invention's embodiments clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only a small part of the embodiments of the present invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0106] A method for efficient cutting of continuously cast irregular-shaped billets includes the following steps:

[0107] (1) Data preparation: collect real-time data during continuous casting production, including real-time values ​​of key process parameters such as actual casting speed, actual liquid level and secondary cooling water flow rate, in order to calculate the parameter changes during the liquid-solid conversion process.

[0108] (2) Calculate the actual time period corresponding to the billet, accumulate the casting speed in the time direction, calculate the cumulative length of the billet in real time, and back-calculate the actual time corresponding to the billet when it is in the liquid state;

[0109] (3) Heat flux density calculation: Based on the corresponding time and process parameters when the billet is in the liquid state, the heat flux density of each billet is calculated;

[0110] (4) When changing the nozzle / tundish, find the correspondence between the nozzle / tundish changing operation time and the fire cutting time of the affected billet to determine the affected billet;

[0111] (5) Calculate the billet cutting, monitor the state of molten steel and the distribution of defects in real time, and dynamically calculate the cutting scheme in combination with process constraints.

[0112] Step (1) includes the following steps:

[0113] The set value of the casting speed and the actual value of the casting speed of the continuous casting machine are collected in real time as the basic data for modeling;

[0114] Real-time crystallizer liquid level information is collected as the basic data for modeling, and the real-time value of liquid level fluctuation is calculated by difference.

[0115]

[0116] in This represents the liquid level fluctuation value. This is the actual value of the liquid level in the crystallizer; Set the liquid level setting for the crystallizer;

[0117] Real-time acquisition of key data on real-time cooling water flow in the secondary cooling zone.

[0118] In step (2), after the casting speed increases, the length of the billet passing through the casting machine inlet is accumulated in real time, and then the corresponding billet cutting information is generated according to the real-time signal of the fire cutter clamp.

[0119]

[0120] in:

[0121] This refers to the total cumulative length of the billet passing through the casting machine inlet; The lifting time is the time required for the speed to increase. This refers to the time for the pull speed to return to zero. For instantaneous acceleration; This is the interval time (1 second in this case);

[0122] When the cutting occurs, calculate the first... The cumulative length information of the ingot casting is calculated as follows:

[0123]

[0124] in: For the first The cumulative length of the billet in the block; The lifting time is the time required for the speed to increase. The current time; For instantaneous acceleration; This is the interval time, which is 1 second here; For the first Length of the ingot casting;

[0125] Based on the change in the remaining length in the fire-cutting machine Retrospectively calculate the entry time of each casting billet. , billet casting end time and duration of passage The backtracking method is as follows:

[0126] 1) Selecting the billet entry time

[0127] a) If this is the first cast billet, then That is, the lifting speed and time;

[0128] b) If it is not the first cast billet, then That is, the end time of the previous casting billet;

[0129] 2) Duration of billet back-pushing

[0130] a) Traversing the first Cumulative length of ingot casting at various time points ;

[0131] b) When When the changed length is less than or equal to the cumulative length, the time at which this occurs is the billet casting end time. ;

[0132] c) Calculate the billet transit time

[0133]

[0134] Obtain the entry time from the billet End time of billet casting Information on liquid level fluctuations and key processes of secondary cooling water.

[0135] In step (3), the heat flux density is calculated as follows:

[0136]

[0137] in: Heat flux density; This refers to the specific heat capacity of the cooling water. This refers to the cooling water flow rate; For changes in cooling water temperature; This refers to the outlet temperature of the cooling water. This refers to the inlet temperature of the cooling water. The total contact area, For the width area, For narrow face area;

[0138] The cooling water throughput is calculated cumulatively from the cooling water flow rate, as follows:

[0139]

[0140] in: This refers to the cooling water flow rate; This refers to the start time of billet casting; This refers to the end time of billet casting; This refers to the instantaneous cooling water flow rate; This is the interval time, which is 1 second here.

[0141] Step (5) includes the following steps:

[0142] 1) Defect data acquisition: Real-time monitoring of crystallizer status, casting speed, and defect points or sections during nozzle / tundish replacement to obtain the defect location of the billet. Defect data is then assessed and quantified. For any position x along the length of the billet, a quality confidence level is defined.

[0143]

[0144] in: The process fluctuation index is a statistical analysis of abnormal conditions in parameters such as casting speed, liquid level, and secondary cooling flow rate over a corresponding time period. For the corresponding abnormal segment of the billet parameters, then ;

[0145] The heat flux index is used to inversely deduce the solidification front stability from the integral of the heat flux density. For the corresponding segregation / crack risk impact section, then ;

[0146] Mark the event disturbance if For the section affected by replacing the water inlet / intermediate refrigerant, then ;

[0147] This provides a data foundation for calculating the overall defects of the billet and for subsequent sliding window calculations.

[0148] For defective data, the original data undergoes secondary processing using a defect filling mechanism:

[0149] a) When the defect interval does not reach the minimum cutting length, the defects are considered to be connected;

[0150] b) When the defect interval reaches the minimum cutting length or exceeds the maximum cutting length, no operation is performed on the defect data.

[0151] 2) Sliding window constrained dynamic programming: Based on the defect data, a dynamic programming mechanism is designed as follows:

[0152] a) Discrete segmentation: The 30-meter billet is discretized into several segments, each 0.5 meters long, and the defect locations are marked.

[0153] b) Define state variables: Traverse upwards from the cutting direction to record the current cutting start point and the remaining length to be cut;

[0154] c) Define the objective function: maximize the effective billet length and minimize the segment containing billet defects;

[0155] d) Constraints: The length of each segment is within the process range and avoids areas with dense defects; the minimum remaining normal segment of the cast billet;

[0156] 3) Optimize the solution by using dynamic programming recursive calculation to derive the optimal cutting point from the end of the billet, ensuring that each cut is within the compliant length range and that the impact of defects is minimized;

[0157] a) Calculation method for the defect front end, i.e., the first billet to be included:

[0158] When any defect is detected, wait for the last billet to be cut, then divide the remaining normal billets into the smallest cutting units that meet the conditions, while ensuring that billet waste is minimized.

[0159] The calculation method is as follows:

[0160]

[0161] in: This represents the total length of the normal cast billet to be calculated. This indicates the cutting length of each segment of the cast billet. Represents the number of segments. Remaining length , Minimum cutting length;

[0162] To ensure the cutting length of each section of the cast billet. exist Between meters, length The remaining billet length must fluctuate within a reasonable range according to the planned length. The optimal cutting method is to make it as small as possible;

[0163] Traversing the fixed length within a reasonable range Calculate the length of the billet to meet the requirements, and follow the... The remaining length of the cast billet after cutting is [length]. Minimum, record minimum The following fixed length This completes the cutting of subsequent normal segments;

[0164] b) Calculation method for defective middle section:

[0165] When the head of the defective billet enters the cutting position, skip all defective billets and cut the defective section as little as possible within a reasonable billet length range; if the defect interval is within... Between meters, the internal normal casting billet is cut in the same way as the defective front end;

[0166] Based on the filled defect segment data, defect segment cutting calculations are performed, satisfying the following formula:

[0167] First calculate the minimum number of cuts required. part, For positive integers:

[0168]

[0169] in: This represents the total length of the abnormal billet to be calculated. Represents the number of segments. Remaining length , This is the maximum cutting length;

[0170] Based on the calculated number of segments Calculate the fixed length when cutting uniformly. :

[0171]

[0172] in: This represents the total length of the abnormal billet to be calculated. Represents the number of segments. This is the adjusted fixed length;

[0173] If the defect interval is greater than If the defect segment is cut off, the calculation of a new defect segment begins.

[0174] c) Calculation method for the defective end-stage, i.e., the later-entering billet:

[0175] When the continuous defects end, wait for the defect end position to leave the rolling mill, cut at the end position, calculate the subsequent normal cutting position and repeat the normal cutting process;

[0176] 4) Real-time adjustment, online updating of the cutting plan, and sending instructions to the flame cutting machine for execution, dynamically adjusting the fixed length;

[0177] 5) Calculation process: Real-time adjustment of billet cutting; determination of whether the current cutting scheme matches the planned scheme; if defects are concentrated, adjustment to a more reasonable cutting scheme:

[0178] After casting begins, the current drawing length is accumulated in real time, the process parameters during the drawing process are monitored, and defect information is recorded at any time. The drawn billet is dynamically planned in real time to obtain the optimal billet cutting scheme. Combined with the current fixed length of the flame cutter, it is determined whether the optimal cutting can be achieved. If it can, the cutting is carried out normally. If not, the fixed length of the flame cutter needs to be adjusted according to the optimal scheme, and the billet with dense defects is removed first.

[0179] In practical applications, this invention achieves efficient cutting by collecting and analyzing key data. Its main principle is to solve the core problems of liquid-solid conversion and cutting calculation in the following five aspects.

[0180] Select the process parameters for the corresponding time period of the billet based on the flame cutting signal.

[0181] During continuous casting, it is necessary to select and calculate the actual time period corresponding to the billet based on the flame cutting signal. The billet position is determined by combining the continuous casting machine length and casting speed, and key parameters within this time period (such as casting speed, secondary cooling water flow rate, and crystallizer temperature) are extracted. The liquid steel events are converted into solid-state events to ensure data matches the actual solidification state of the billet. Simultaneously, the time synchronization and accuracy of the position calculation are verified. Finally, key billet information, including flame cutting time, billet position, and process parameters, is output to support quality analysis and process optimization.

[0182] Liquid-solid transformation events

[0183] Liquid-solid transformation refers to the critical phase transition process in continuous casting where molten steel changes from a liquid to a solid state. When molten steel flows from the tundish into the crystallizer, it gradually solidifies through contact with the copper plate and forced cooling in the secondary cooling zone, forming a billet shell and ultimately completing the liquid-solid phase transition to create a solid billet with a stable shape and internal structure. This process involves complex phenomena such as heat transfer, solidification shrinkage, and microstructure evolution, directly affecting the surface quality, internal defects (such as cracks and segregation), and mechanical properties of the billet. It is a core aspect of continuous casting process control.

[0184] Heat flux density calculation

[0185] Analyzing key parameters of the billet solidification process is used to quantify heat transfer per unit time per unit area (typically expressed in kW / m²). 2 In the crystallizer zone, heat flux density can be calculated by measuring the temperature difference between the inlet and outlet of the cooling water, the flow rate, and the temperature change of the copper plate, combined with a heat transfer model. In the secondary cooling zone, it is determined based on the cooling efficiency of the spray water, the surface temperature of the billet, and radiative heat dissipation. Accurate calculation of heat flux density helps optimize cooling strategies, prevents defects such as cracks and bulging caused by local overheating or overcooling, and provides important basis for the digital control of continuous casting processes.

[0186] Special handling when changing the water inlet / intermediate roll

[0187] In continuous casting production, changing the nozzle or tundish is a non-steady-state operation, which can cause sudden changes or abnormal fluctuations in process parameters (such as casting speed, temperature, and cooling water flow). To better describe the actual changes in these parameters, special data processing is required.

[0188] (1) Data segmentation and marking: Set up a buffer zone before and after the time point of water exchange / intermediate package, and mark the data of this period separately as "transition phase" to avoid confusion with normal production data.

[0189] (2) Outlier filtering: Remove invalid or outlier data caused by operation interruption (such as sudden drop in pulling speed or failure of temperature measurement) to prevent interference with statistical analysis.

[0190] (3) Process parameter interpolation / smoothing: Use moving average or linear interpolation to smooth the transition of key parameters (such as crystallizer temperature and secondary cooling water flow) to ensure data continuity.

[0191] (4) Event correlation analysis: Combine the operation log to analyze the change trend of billet quality (such as cracks and inclusions) before and after the water nozzle is changed, and optimize the ladle changing process.

[0192] The above processing can reduce the interference of non-steady-state data on model training or process control, and at the same time provide a reliable basis for process improvement.

[0193] High-efficiency billet cutting method

[0194] In the continuous casting process of steel, the solidification state of molten steel located in the roller conveyor is monitored and analyzed in real time. By monitoring liquid level fluctuations, cooling water flow, and other parameters through detection equipment, quality data of the molten billet can be obtained, and the location of abnormal points with defects such as cracks, inclusions, or segregation can be accurately pinpointed.

[0195] Based on this detection data, the intelligent billet cutting algorithm comprehensively considers multiple optimization objectives such as production plan requirements, maximizing yield, and defect avoidance. Using optimization methods such as dynamic programming, it calculates the optimal cutting scheme. This scheme needs to determine parameters such as the start and end positions of the cuts, the cutting sequence, and the cutting length to ensure that while removing defective portions, metal loss is minimized, and the process requirements for billet dimensions in subsequent rolling processes are met. The system also continuously optimizes the cutting strategy based on real-time production changes, improving production efficiency and product quality.

[0196] The main steps are as follows:

[0197] Data preparation

[0198] Collect real-time data during continuous casting production, including real-time values ​​of key process parameters such as actual casting speed, actual liquid level, and secondary cooling water flow rate, in order to calculate parameter changes during the liquid-solid conversion process.

[0199] Process parameter information

[0200] By obtaining real-time information on continuous casting processes such as casting speed, crystallizer information, and cooling water flow rate, the quality of the cast billet can be inferred.

[0201] Table of continuous casting process parameters

[0202]

[0203] Speed

[0204] In continuous casting, casting speed is one of the core process parameters, directly determining the residence time of molten steel in the crystallizer and the solidification behavior of the billet. Proper control of the casting speed has a significant impact on the surface quality, internal structure, and production efficiency of the billet. Typically, the casting speed needs to be optimized based on the characteristics of the steel grade, the cross-sectional dimensions of the billet, and the cooling conditions, ensuring sufficient solidification time to avoid surface cracks and internal defects while also considering production efficiency.

[0205] In actual production, the stability of the casting speed is particularly critical. Therefore, the set value of the casting speed and the actual value of the continuous casting machine casting speed were collected in real time as the basic data for modeling.

[0206] Crystallizer liquid level information

[0207] The liquid level in the crystallizer is a key parameter for monitoring the continuous casting process, directly reflecting the dynamic equilibrium of molten steel within the crystallizer. The stability of the liquid level has a decisive impact on the surface quality of the cast billet and production safety. By adjusting the stopper rod or sliding gate opening in real time, the liquid level can be maintained under transitional conditions such as changes in casting speed and tundish replacement, ensuring the production of high-quality cast billets.

[0208] Therefore, real-time crystallizer liquid level information was collected as the basic data for modeling. The real-time value of liquid level fluctuation was calculated by the difference.

[0209]

[0210] in:

[0211] This represents the liquid level fluctuation value. This is the actual value of the liquid level in the crystallizer; Set the liquid level setting for the crystallizer.

[0212] Cooling water flow rate

[0213] The secondary cooling water flow rate is a core parameter for controlling the solidification process of the billet in continuous casting, and its adjustment accuracy directly affects the internal quality and surface integrity of the billet. As the most important cooling control method in the secondary cooling zone, the secondary cooling water flow rate needs to be dynamically matched according to the characteristics of the steel grade, the cross-sectional dimensions of the billet, and the casting speed.

[0214] To this end, key data on real-time cooling water flow rate in the secondary cooling zone were collected.

[0215] Calculation method for the actual corresponding time period of the billet

[0216] To simulate events occurring during the liquid phase of the billet, it is first necessary to determine the real-time position of each billet within the continuous casting machine. However, due to the length of the continuous casting machine itself, the critical time points of the billet are usually only determined after it has been cut. Therefore, it is necessary to extrapolate the actual time and position of the billet within the continuous casting machine.

[0217] This invention uses the cumulative casting speed over time to calculate the cumulative length of the billet in real time, and then extrapolates the actual corresponding time when the billet is in the molten state. When the casting speed increases, the length of the billet passing through the casting machine inlet is accumulated in real time, and then the corresponding billet cutting information is generated based on the real-time signal from the flame cutter clamp.

[0218]

[0219] in:

[0220] This refers to the total cumulative length of the billet passing through the casting machine inlet; The lifting time is the time required for the speed to increase. This refers to the time for the pull speed to return to zero.

[0221] For instantaneous acceleration; This is the interval time (1 second in this case).

[0222] When the cutting occurs, the first... The cumulative length information of the ingot casting is calculated as follows.

[0223]

[0224] in:

[0225] For the first The cumulative length of the billet in the block; The lifting time is the time required for the speed to increase. The current time;

[0226] For instantaneous acceleration; This is the interval time (1 second in this case). For the first Length of the ingot casting.

[0227] Based on the change in the remaining length in the fire-cutting machine Retrospectively calculate the entry time of each casting billet. , billet casting end time , through duration .

[0228] The backtracking method is as follows:

[0229] Select billet entry time

[0230] If it is the first cast billet, then That is, the lifting speed and time.

[0231] If it is not the first cast billet, then That is, the end time of the previous casting.

[0232] Time for back-pushing of billet

[0233] Traversing the first Cumulative length of ingot casting at various time points .

[0234] when When the changed length is less than or equal to the cumulative length, the time at which this occurs is the billet casting end time. .

[0235] Calculate the billet transit time .

[0236]

[0237] Obtain the entry time from the billet End time of billet casting Key process information such as liquid level fluctuations and secondary cooling water.

[0238] By using the above methods, the event state that occurred when the solid billet was in the liquid state is restored, the liquid-solid conversion is completed, and the purpose of analyzing the billet condition and improving the billet quality is achieved.

[0239] Heat flux density calculation

[0240] Heat flux density analysis in continuous casting machines is a core aspect of continuous casting process optimization, directly impacting billet quality (such as cracks and segregation) and production efficiency. Using the corresponding time and process parameters when the billet is in a liquid state obtained from the above analysis, the heat flux density of each billet can be calculated as follows:

[0241]

[0242] in:

[0243] Heat flux density; This refers to the specific heat capacity of the cooling water. This refers to the cooling water flow rate;

[0244] For changes in cooling water temperature; This refers to the outlet temperature of the cooling water. This refers to the inlet temperature of the cooling water.

[0245] The total contact area, For the width area, It represents the area of ​​the narrow face.

[0246] The cooling water throughput needs to be calculated cumulatively from the cooling water flow rate, and the calculation method is as follows:

[0247]

[0248] in:

[0249] This refers to the cooling water flow rate; This refers to the start time of billet casting; This refers to the end time of billet casting;

[0250] This refers to the instantaneous cooling water flow rate; This is the interval time (1 second in this case).

[0251] Handling procedures when changing water inlets / intermediate rolls

[0252] During the casting process, situations may occur where the tundish nozzle or tundish is changed, affecting various process parameters of the cast billet. Therefore, it is necessary to pinpoint the specific cast billet affected by this special operation. Analysis of the continuous casting diagram reveals that, coinciding with the actual time period for billet positioning, and due to the influence of the roller conveyor length, it is necessary to find the correspondence between the tundish nozzle / tundish change operation time and the heat-cutting time of the affected billet in order to identify the affected billet.

[0253] During the casting process, upon receiving a signal to change the sprue / tundish, record the time and location information, marking it as a defective billet segment. Clarify the actual condition of the liquid billet on the roller conveyor during the sprue / tundish change operation, and understand the impact of this special operation on the actual billet. Perform billet length verification during tundish change to prevent length deviations caused by prolonged accumulated casting speed.

[0254] By determining the actual impact of changing the tundish / intermediate ladle on the liquid billet, and then calculating the billet information based on the actual corresponding time period of the billet, the specific impact of special operations on the billet can be located, thereby enabling precise quality control of the billet.

[0255] High-efficiency billet cutting algorithm

[0256] Based on the corresponding defect information of process parameters, this paper proposes an efficient billet cutting optimization method based on sliding window constraint dynamic programming. By monitoring the state of molten steel and defect distribution in real time, combined with process constraints (such as effective cutting length of 4-12 meters), the optimal cutting scheme is dynamically calculated to maximize the proportion of qualified billets and effectively improve the yield.

[0257] Defect data collection:

[0258] Based on the above method, the status of the crystallizer, casting speed, and defect points or sections such as tundish / intermediate ladle replacement can be monitored in real time to obtain the location of defects in the billet.

[0259] According to the established rules, defect data is judged and quantified. For any position x (unit: meter) along the length of the billet, its quality confidence level is defined:

[0260]

[0261] in:

[0262] This is a process fluctuation index, based on statistical analysis of abnormal situations in parameters such as casting speed, liquid level, and secondary cooling flow rate over a corresponding time period. For the corresponding abnormal segment of the billet parameters, then ;

[0263] The heat flux index is used to inversely deduce the solidification front stability from the integral of the heat flux density. For the corresponding segregation / crack risk impact section, then ;

[0264] Mark the event disturbance if For the section affected by replacing the water inlet / intermediate refrigerant, then ;

[0265] This provides a data foundation for calculating the overall defects of the billet and for subsequent sliding window calculations.

[0266] like Figures 5 to 7 The x-axis of the curve represents the distance to the fire cut (unit: cm). The Boolean values ​​of the three curves—the casting speed defect curve, the liquid level fluctuation defect curve, and the nozzle / tundish replacement defect curve—are ORed to obtain the slab comprehensive evaluation curve, as shown below. Figure 8 This curve can be used to locate defects and perform optimized cutting calculations on uncut billets.

[0267] For defective data, the original data needs to be processed a second time, and a defect filling mechanism needs to be designed:

[0268] When the defect interval does not reach the minimum cutting length, the defects are considered to be connected.

[0269] When the defect interval reaches the minimum cutting length or exceeds the maximum cutting length, no operation is performed on the defect data.

[0270] like Figure 9 The red arrow indicates the defect filling location. The area indicated by the red arrow does not reach the minimum casting billet range, so it is filled as a defect area.

[0271] Sliding window constraint dynamic programming mechanism:

[0272] Based on the defect data, a dynamic programming mechanism is designed as follows:

[0273] Discrete segmentation: The 30-meter billet is discretized into several segments, each 0.5 meters long, and the defect locations are marked.

[0274] Define state variables: Traverse upwards from the cutting direction to record the current cutting start point and the remaining length to be cut.

[0275] Define the objective function as: maximize the effective billet length and minimize the segment containing billet defects.

[0276] Constraints: The length of each segment must be within the process range and avoid areas with dense defects, with the minimum remaining normal segment of the cast billet.

[0277] Optimization solution:

[0278] Dynamic programming recursive calculation is used to derive the optimal cutting point from the end of the billet in reverse order, ensuring that each cut is within the compliant length range and that the impact of defects is minimized.

[0279] Defect front-end (first-entering billet) calculation method:

[0280] When any defect is detected, wait for the last billet to be cut, divide the remaining normal billets into the smallest cutting units that meet the conditions, and ensure that billet waste is minimized.

[0281] The calculation method is as follows:

[0282]

[0283] in: This represents the total length of the normal cast billet to be calculated. This indicates the cutting length of each segment of the cast billet. Represents the number of segments. Remaining length , This is the minimum cutting length.

[0284] To ensure the cutting length of each section of the cast billet. exist Between meters, length The remaining billet length must fluctuate within a reasonable range according to the planned length. The optimal cutting method is to cut as small as possible.

[0285] Traversing the fixed length within a reasonable range Calculate the length of the billet to meet the requirements, and follow the... The remaining length of the cast billet after cutting is [length]. Minimum, record minimum The following fixed length This completes the cutting of the subsequent normal segments.

[0286] Defect mid-section calculation method:

[0287] When the head of the defective billet enters the cutting position, skip all defective billets and cut the defective section as little as possible within a reasonable billet length range; if the defect interval is within... Between meters, the internal normal casting billet is cut in the same way as the defective front end.

[0288] Based on the filled defect segment data, defect segment cutting calculations are performed, satisfying the following formula:

[0289] First calculate the minimum number of cuts required. part, For positive integers:

[0290]

[0291] in: This represents the total length of the abnormal billet to be calculated. Represents the number of segments. Remaining length , This represents the maximum cutting length.

[0292] Based on the calculated number of segments Calculate the fixed length when cutting uniformly. :

[0293]

[0294] in: This represents the total length of the abnormal billet to be calculated. Represents the number of segments. This is the adjusted standard length.

[0295] If the defect interval is greater than If the defect segment is cut off, the calculation of a new defect segment begins.

[0296] Calculation method for defects at the rear end (later-entering billet):

[0297] When the continuous defects end, wait for the defect end position to leave the rolling mill, cut at the end position, calculate the subsequent normal cutting position, and repeat the normal cutting process.

[0298] Real-time adjustments:

[0299] Based on the above calculation method, the cutting scheme is updated online, and instructions are sent to the flame cutting machine for execution, dynamically adjusting the fixed length.

[0300] Calculation process:

[0301] The above methods can be used to adjust the billet cutting in real time, determine whether the current cutting scheme is consistent with the planned scheme, and if there are many defects, adjust to a more reasonable cutting scheme to reduce the scrap billet.

[0302] After casting begins, the current drawn length is accumulated in real time, the process parameters during the casting process are monitored, and defect information is recorded at any time. The drawn billet is dynamically planned in real time to obtain the optimal billet cutting scheme. Combined with the current fixed length of the flame cutter, it is determined whether the optimal cutting can be achieved. If it can, normal cutting is performed; if not, the fixed length of the flame cutter needs to be adjusted according to the optimal scheme, and the billet with dense defects is removed first.

[0303] This invention can perform data simulation on all billets in continuous casting, optimize the cutting of areas with dense defects, record all key time nodes, generate billet information quality reports, and conduct detailed quality control of billets, with the following beneficial effects:

[0304] (1) This invention improves the precision of quality control. By tracking billet parameters in real time (such as temperature, casting speed, cooling intensity, crystallizer vibration, etc.) and combining them with fire cutting signals (cutting position, time), the location and process cause of defects (such as cracks, segregation, inclusions) can be quickly located. It can dynamically adapt to production fluctuations (such as changing the nozzle, changes in casting speed) and improve cutting flexibility.

[0305] (2) This invention reduces the scrap rate. When parameters are abnormal (such as excessively high cooling water temperature), it can provide early warning of equipment wear, avoid scrapping the entire billet, and reduce unplanned downtime. When process defects are concentrated, the cutting strategy is dynamically adjusted, which effectively reduces billet waste and lowers production costs.

[0306] (3) The present invention generates a quality analysis report, which can statistically analyze the distribution of defect types and the correlation between process parameters and quality, providing a basis for process optimization.

[0307] This invention analyzes the overall casting length by using the cumulative amount of casting speed, eliminating casting stops caused by special operations. It can automatically identify castings with abnormal parameters, castings affected by special operations, and castings whose length does not meet the requirements. It analyzes the on-site production status in real time, dynamically optimizes the cutting strategy, and provides on-site production technical guidance.

[0308] Example 1

[0309] Information on the second casting at 02:41:42 on June 24, 2025.

[0310] Table of billet information

[0311]

[0312] Casting speed of each billet

[0313] By accumulating the casting speed throughout the continuous casting process, the cumulative casting length information can be obtained, and the cumulative length curve is shown below. Figure 10 The green line represents the remaining length curve inside the casting machine; the yellow line indicates the cutting time and the fixed length.

[0314] The handling of the abnormal furnace speed is as follows: Figure 11-12 For handling of abnormal liquid level fluctuation curves, see [link to relevant documentation]. Figure 13-14 For handling of abnormal curves in the secondary cooling water, see [link / reference]. Figure 15-16 ,

[0315] By processing the parameter curve data, a defect statistics curve is obtained. Based on this data, the cutting is reasonably optimized to ensure that the remaining normal billet section is minimized. The comprehensive defect curve is as follows: Figure 17 .

[0316] The following cutting curve is obtained by optimizing the algorithm. The extra curve represents the start-up state of the fire cutter, and the rising edge represents the cutting position. The fixed length is optimized to 7.05m based on the requirements and the defect location. The defective section of the billet is cut and optimized. The defect length is 17m, and it should be cut into at least two sections. The fixed length within the defective section is calculated to be 8.5m to ensure that normal cutting begins at the end of the defect.

[0317] Example 2

[0318] 4-strand casting information at 01:37:44 on 2025-06-21

[0319] Table of billet information

[0320]

[0321] For details on casting speed for each billet, and the periods and handling of abnormal casting speeds, please refer to [link / reference]. Figures 19-20 For handling of abnormal liquid level fluctuation curves, see [link to relevant documentation]. Figure 21-22 By processing parameter curve data, a defect statistics curve is obtained. Using a defect curve filling mechanism, the defect interval is kept below the minimum effective billet length. Based on this data, the cutting is rationally optimized to ensure the minimum remaining normal billet section.

[0322] Based on the processed comprehensive defect curve, the cutting positions before and during defects are calculated according to the designed algorithm, and the fixed length is optimized to ensure that the waste of the casting billet is minimized.

[0323] The following cutting curve is obtained after optimization based on the algorithm. The extra curve represents the start-up state of the fire cutter, and the rising edge represents the cutting position. The optimized length is 8.05m based on the requirements and the defect location, but there is still a 2.5m normal billet section left. The defective billet section is cut and optimized. The defect length is 17.5m. In addition, including the remaining 2.5m normal billet, it is necessary to calculate comprehensively and cut it into at least two sections. The fixed length within the defective section is calculated to be 10m to ensure that normal cutting begins at the end of the defect.

[0324] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. All equivalent changes or modifications made in accordance with the spirit and essence of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for efficient cutting of continuously cast irregular-shaped billets, characterized in that... Includes the following steps: (1) Data preparation: collect real-time data during continuous casting production, including real-time values ​​of key process parameters such as actual casting speed, actual liquid level and secondary cooling water flow rate, in order to calculate the parameter changes during the liquid-solid conversion process. (2) Calculate the actual time period corresponding to the billet, accumulate the casting speed in the time direction, calculate the cumulative length of the billet in real time, and back-calculate the actual time corresponding to the billet when it is in the liquid state; (3) Heat flux density calculation: Based on the corresponding time and process parameters when the billet is in the liquid state, the heat flux density of each billet is calculated; (4) When changing the nozzle / tundish, find the correspondence between the nozzle / tundish changing operation time and the fire cutting time of the affected billet to determine the affected billet; (5) Calculate the billet cutting, monitor the state of molten steel and the distribution of defects in real time, and dynamically calculate the cutting scheme in combination with process constraints.

2. The method for efficient cutting of continuously cast irregular-shaped billets according to claim 1, characterized in that: Step (1) includes the following steps: The set value of the casting speed and the actual value of the casting speed of the continuous casting machine are collected in real time as the basic data for modeling; Real-time crystallizer liquid level information is collected as the basic data for modeling, and the real-time value of liquid level fluctuation is calculated by difference. in This represents the liquid level fluctuation value. This is the actual value of the liquid level in the crystallizer; Set the liquid level setting for the crystallizer; Real-time acquisition of key data on real-time cooling water flow in the secondary cooling zone.

3. The method for efficient cutting of continuously cast irregular-shaped billets according to claim 1, characterized in that: In step (2), after the casting speed increases, the length of the billet passing through the casting machine inlet is accumulated in real time, and then the corresponding billet cutting information is generated according to the real-time signal of the fire cutter clamp. in: This refers to the total cumulative length of the billet passing through the casting machine inlet; The lifting time is the time required for the speed to increase. This refers to the time for the pull speed to return to zero. For instantaneous acceleration; This is the interval time (1 second in this case); When the cutting occurs, calculate the first... The cumulative length information of the ingot casting is calculated as follows: in: For the first The cumulative length of the billet in the block; The lifting time is the time required for the speed to increase. The current time; For instantaneous acceleration; This is the interval time, which is 1 second here; For the first Length of the ingot casting; Based on the change in the remaining length in the fire-cutting machine Retrospectively calculate the entry time of each casting billet. , billet casting end time and duration of passage The backtracking method is as follows: Selecting the billet entry time a) If this is the first cast billet, then That is, the lifting speed and time; b) If it is not the first cast billet, then That is, the end time of the previous casting billet; Time for the billet to be pushed back through a) Traversing the first Cumulative length of ingot casting at various time points ; b) When When the changed length is less than or equal to the cumulative length, the time at which this occurs is the billet casting end time. ; c) Calculate the billet transit time Obtain the entry time from the billet End time of billet casting Information on liquid level fluctuations and key processes of secondary cooling water.

4. The method for efficient cutting of continuously cast irregular-shaped billets according to claim 1, characterized in that: In step (3), the heat flux density is calculated as follows: in: Heat flux density; This refers to the specific heat capacity of the cooling water. This refers to the cooling water flow rate; For changes in cooling water temperature; This refers to the outlet temperature of the cooling water. This refers to the inlet temperature of the cooling water. The total contact area, For the width area, For narrow face area; The cooling water throughput is calculated cumulatively from the cooling water flow rate, as follows: in: This refers to the cooling water flow rate; This refers to the start time of billet casting; This refers to the end time of billet casting; This refers to the instantaneous cooling water flow rate; This is the interval time, which is 1 second here.

5. The method for efficient cutting of continuously cast irregular-shaped billets according to claim 1, characterized in that: Step (5) includes the following steps: Defect data acquisition involves real-time monitoring of the crystallizer status, casting speed, and defect points or sections during nozzle / tundish changes to obtain the defect location of the billet. The defect data is then assessed and quantified, and a quality confidence level is defined for any position x along the length of the billet. in: The process fluctuation index is a statistical analysis of abnormal conditions in parameters such as casting speed, liquid level, and secondary cooling flow rate over a corresponding time period. For the corresponding abnormal segment of the billet parameters, then ; The heat flux index is used to inversely deduce the solidification front stability from the integral of the heat flux density. For the corresponding segregation / crack risk impact section, then ; Mark the event disturbance if For the section affected by replacing the water inlet / intermediate refrigerant, then ; This provides a data foundation for calculating the overall defects of the billet and for subsequent sliding window calculations. For defective data, the original data undergoes secondary processing using a defect filling mechanism: a) When the defect interval does not reach the minimum cutting length, the defects are considered to be connected; b) When the defect interval reaches the minimum cutting length or exceeds the maximum cutting length, no operation is performed on the defect data; Sliding window constrained dynamic programming: Based on defect data, a dynamic programming mechanism is designed as follows: a) Discrete segmentation: The 30-meter billet is discretized into several segments, each 0.5 meters long, and the defect locations are marked. b) Define state variables: Traverse upwards from the cutting direction to record the current cutting start point and the remaining length to be cut; c) Define the objective function: maximize the effective billet length and minimize the segment containing billet defects; d) Constraints: The length of each segment is within the process range and avoids areas with dense defects; the minimum remaining normal segment of the cast billet; The optimization solution uses dynamic programming recursive calculation to derive the optimal cutting point from the end of the billet, ensuring that each cut is within the compliant length range and that the impact of defects is minimized. a) Calculation method for the defect front end, i.e., the first billet to be included: When any defect is detected, wait for the last billet to be cut, then divide the remaining normal billets into the smallest cutting units that meet the conditions, while ensuring that billet waste is minimized. The calculation method is as follows: in: This represents the total length of the normal cast billet to be calculated. This indicates the cutting length of each segment of the cast billet. Represents the number of segments. Remaining length , Minimum cutting length; To ensure the cutting length of each section of the cast billet. exist Between meters, length The remaining billet length must fluctuate within a reasonable range according to the planned length. The optimal cutting method is to make it as small as possible; Traversing the fixed length within a reasonable range Calculate the length of the billet to meet the requirements, and follow the... The remaining length of the cast billet after cutting is [length]. Minimum, record minimum The following fixed length This completes the cutting of subsequent normal segments; b) Calculation method for defective middle section: When the head of the defective billet enters the cutting position, skip all defective billets and cut the defective section as little as possible within a reasonable billet length range; if the defect interval is within... Between meters, the internal normal casting billet is cut in the same way as the defective front end; Based on the filled defect segment data, defect segment cutting calculations are performed, satisfying the following formula: First calculate the minimum number of cuts required. part, For positive integers: in: This represents the total length of the abnormal billet to be calculated. Represents the number of segments. Remaining length , This is the maximum cutting length; Based on the calculated number of segments Calculate the fixed length when cutting uniformly. : in: This represents the total length of the abnormal billet to be calculated. Represents the number of segments. This is the adjusted fixed length; If the defect interval is greater than If the defect segment is cut off, the calculation of a new defect segment begins. c) Calculation method for the defective end-stage, i.e., the later-entering billet: When the continuous defects end, wait for the defect end position to leave the rolling mill, cut at the end position, calculate the subsequent normal cutting position and repeat the normal cutting process; The cutting scheme is updated online and adjusted in real time, and instructions are sent to the flame cutting machine for execution, dynamically adjusting the fixed length. The calculation process involves real-time adjustments to the billet cutting, determining whether the current cutting scheme matches the planned scheme, and adjusting to a more reasonable cutting scheme if there are numerous defects. After casting begins, the current drawing length is accumulated in real time, the process parameters during the drawing process are monitored, and defect information is recorded at any time. The drawn billet is dynamically planned in real time to obtain the optimal billet cutting scheme. Combined with the current fixed length of the flame cutter, it is determined whether the optimal cutting can be achieved. If it can, the cutting is carried out normally. If not, the fixed length of the flame cutter needs to be adjusted according to the optimal scheme, and the billet with dense defects is removed first.

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