Prediction method, prediction device and equipment for internal defect length of continuous casting billet, storage medium and program product

Abstract

The invention discloses a continuous casting billet internal defect length prediction method and device, equipment, a storage medium and a program product. The prediction method comprises the steps of obtaining production data of a target casting blank, wherein the production data comprises the type of the target casting blank, the continuous casting speed V0 and the thickness d of the target casting blank; the predicted processing time T under the abnormal condition is obtained, and the first continuous casting speed V1 under the abnormal condition and the operation time t2 under the first continuous casting speed V1 are obtained according to the predicted processing time T; and according to the production data, the first continuous casting speed V1 and a defect length prediction model, the length of the internal quality defect of the target casting blank is obtained, and the defect length prediction model is constructed based on a solidification calculation formula. According to the prediction method, under the condition of continuous production, the internal quality defect length under the condition of abnormal speed reduction of continuous casting is accurately predicted, so that internal quality control of the continuous casting billet is effectively guided, and stable production is realized.

Description

Technical Field

[0001] This application belongs to the technical field of steel continuous casting production, and particularly relates to a method, prediction device, equipment, storage medium and program product for predicting the length of internal defects in continuously cast billets. Background Technology

[0002] Continuous casting is a crucial step in steel production. During continuous casting, abnormal situations such as equipment failure, fluctuations in molten steel temperature, or operational errors may necessitate adjustments to the casting speed, particularly speed reduction. Changes in casting speed directly affect the solidification process of the billet, leading to variations in the length of the solidification end (liquid core).

[0003] The continuity of the continuous casting production process has a significant impact on the utilization rate and energy consumption of the entire equipment. Generally, even in the event of an accident or abnormality, other processes are adjusted to resolve the situation, and production interruption is generally avoided. Therefore, how to achieve continuous casting production while maintaining stable quality of the continuously cast billets under abnormal conditions is a key research direction. Summary of the Invention

[0004] This application provides a method, device, equipment, storage medium, and program product for predicting the length of internal defects in continuously cast billets. Under continuous production conditions, it can accurately predict the range of internal quality defect lengths under abnormal speed reduction conditions in continuous casting, thereby effectively guiding the internal quality control of continuously cast billets, reducing quality risks, and achieving stable production and quality of continuously cast billets.

[0005] In a first aspect, embodiments of this application provide a method for predicting the length of internal defects in continuously cast billets, the method comprising: Obtain the production data of the target billet, including the type of target billet, continuous casting speed V0, and thickness d of the target billet; Obtain the estimated processing time T under abnormal conditions, and based on the estimated processing time T, obtain the first continuous casting speed V1 under abnormal conditions and the running time t2 at the first continuous casting speed V1. Based on production data, the first continuous casting speed V1, and the defect length prediction model, the length of the internal quality defects of the target billet is obtained. The defect length prediction model is constructed based on the solidification calculation formula.

[0006] In some embodiments, the method for constructing a defect length prediction model includes: Based on the continuous casting speed V0 and thickness d, the solidified shell thickness e0 of the target billet and the liquid core length L0 under the continuous casting speed V0 condition are obtained. Based on the solidified shell thickness e0 and the liquid core length L0, and the formula... e0 / L0, we get the angle α; According to the solidification calculation formula e=K The solidified shell thickness e2 during the time interval t0-t2 is obtained; where K is determined according to the type of the target billet. Using formula e0 / L0=(e0-e2) / (L0-L2), to obtain the liquid core length L2 under the condition of the first continuous casting speed V1; Based on the liquid core lengths L0 and L2, the length of the internal quality defect of the target billet under abnormal conditions is obtained as L0-L2.

[0007] In some embodiments, obtaining the first continuous casting speed V1 under abnormal conditions and the running time t2 at the first continuous casting speed V1 based on the expected processing time T includes: In the event of abnormal continuous billet production, the production speed of the billet is adjusted, sequentially going through a deceleration stage, a constant speed stage, and a speed-up stage, wherein: During the deceleration phase, the steel strip decreases from the continuous casting speed V0 to the first continuous casting speed V1 with an acceleration a1, and the duration of the deceleration phase is t1. During the constant speed phase, the running time t2 of the steel strip at the first continuous casting speed V1; During the acceleration phase, the steel strip accelerates from speed V1 to continuous casting speed V0 or second continuous casting speed V2 at an acceleration a2, and the duration of the acceleration phase is t3. Based on the continuous casting speed V0, the expected processing time T, and the durations t1 and t3, determine the running time t2 at the first continuous casting speed V1.

[0008] In some embodiments, the duration t2 of the constant velocity phase is determined according to the following relationship: .

[0009] In some embodiments, V2 is equal to V0.

[0010] In some embodiments, a1 is 0.15~0.25 m / min 2 .

[0011] In some embodiments, a2 is 0.15~0.25 m / min 2 .

[0012] In some embodiments, before obtaining the length of the internal quality defect of the target billet based on production data, the first continuous casting speed V1, and the defect length prediction model, the prediction method further includes: controlling L2 < L1 < L 0， L2 < L3 < L 0， Among them, the liquid core length L1 during continuous casting is measured at duration t1; and the liquid core length L3 during continuous casting is measured at duration t3.

[0013] In some embodiments, the method for determining the liquid core length L1 includes: According to the solidification calculation formula e=K The solidified shell thickness e1 during the time interval t0-t1 is obtained. Using formula e0 / L0=(e0-e1) / (L0-L1), which gives the length L1 of the liquid core during the deceleration phase.

[0014] In some embodiments, the method for determining the liquid core length L3 of the cast billet includes: According to the solidification calculation formula e=K The solidified shell thickness e3 during the time interval t0-t3 is obtained. Using formula e0 / L0=(e0-e3) / (L0-L3), which gives the liquid core length L3 during the acceleration phase.

[0015] Secondly, embodiments of this application provide a device for predicting the length of internal defects in continuously cast billets. The device includes: The acquisition module is used to acquire the production data of the target billet, including the type of the target billet, the continuous casting speed V0, and the thickness d of the target billet. The determination module is used to obtain the estimated processing time T under abnormal conditions, and based on the estimated processing time T, to obtain the first continuous casting speed V1 under abnormal conditions and the running time t2 at the first continuous casting speed V1. The prediction module is used to obtain the length of the internal quality defects of the target billet based on production data, the first continuous casting speed V1, and the defect length prediction model.

[0016] Thirdly, embodiments of this application provide an electronic device, the device including: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements the method for predicting the length of internal defects in continuously cast billets as described above.

[0017] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the method for predicting the length of internal defects in continuously cast billets as described above.

[0018] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform any of the above-mentioned methods for predicting the length of internal defects in continuously cast billets.

[0019] The method for predicting the length of internal defects in continuously cast billets according to this application acquires the production data of the target billet and the estimated processing time under abnormal conditions, and combines this with the continuous casting speed adjustment process to quantitatively predict the change in the position of the solidification end of the continuously cast billet under abnormal conditions. Using a defect length prediction model based on solidification calculation formulas and the input production data and the first continuous casting speed V1, the prediction method of this application can accurately predict the possible length range of internal quality defects in the continuously cast billet when an abnormal speed reduction occurs, thereby providing a basis for the identification, marking, and subsequent process control of abnormal billets.

[0020] Compared with existing technologies, this application can predict internal quality risks in advance during continuous casting without relying on sampling and testing or analysis of the billet. This helps to prevent abnormal billets from entering subsequent rolling processes, reduce the probability of quality accidents, and improve the stability and yield of the continuous casting process. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating the method for predicting the length of internal defects in continuously cast billets provided in the embodiments of this application; Figure 2 This is a schematic diagram of the continuous casting structure showing the crystallizer position in one scenario embodiment provided in this application. Figure 3 This is a graph showing the change in speed versus time under abnormal conditions, provided in an embodiment of this application. Figure 4 This is a schematic diagram of the physical model at different continuous casting speeds provided in the embodiments of this application; Figure 5 This is a schematic diagram of the liquid core length at different continuous casting speeds provided in the embodiments of this application; Figure 6 This is an external view of a continuously cast billet with internal defects provided in an embodiment of this application; Figure 7 This is an external view of a continuously cast billet with no internal defects, provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of the device for predicting the length of internal defects in continuously cast billets provided in the embodiments of this application; Figure 9 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application.

[0023] Explanation of the markings in the attached figures: 800 Prediction device; 801 Acquisition module; 802 Determination module; 803 Prediction module; 901 Processor; 902 Memory; 903 Communication interface; 910 Bus. Detailed Implementation

[0024] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0025] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, predicting method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, predicting method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, predicting method, article, or apparatus that includes the element.

[0026] Under abnormal speed reduction conditions, the solidification end position of the continuously cast billet, the roll gap in the sector section, and the light reduction parameters will all change. The combined effect of these factors may lead to risks to the internal quality of the continuously cast billet, including defects such as center segregation, porosity, and shrinkage cavities, which in turn can cause banded structures or delamination defects.

[0027] Existing technologies often lack accurate quantitative prediction models for assessing internal quality risks under abnormal conditions in continuous casting, making it difficult to accurately determine the length of defects in the billet.

[0028] The uncertainty of internal defects in continuously cast slabs makes it difficult to effectively monitor and isolate abnormal slabs, increasing the risk of rolling slabs with quality risks into finished products and delivering them to customers. This is one of the main reasons for customer quality objections. Therefore, the industry urgently needs a method that can accurately predict the length range of internal defects in continuously cast slabs under abnormal speed reduction conditions.

[0029] To address the problems of the prior art, embodiments of this application provide a method, apparatus, device, storage medium, and program product for predicting the length of internal defects in continuously cast billets. The method for predicting the length of internal defects in continuously cast billets provided in this application embodiment will be described first below.

[0030] Figure 1 A flowchart illustrating a method for predicting the length of internal defects in continuously cast billets according to an embodiment of this application is shown. Figure 1 As shown, a method for predicting the length of internal defects in a continuously cast billet may include the following steps S100 to S300: S100. Obtain the production data of the target billet, including the type of the target billet, the continuous casting speed V0, and the thickness d of the target billet. S200. Obtain the estimated processing time T under abnormal conditions, and based on the estimated processing time T, obtain the first continuous casting speed V1 under abnormal conditions and the running time t2 at the first continuous casting speed V1. S300. Based on production data, the first continuous casting speed V1, and the defect length prediction model, the length of the internal quality defect of the target billet is obtained. The defect length prediction model is constructed based on the solidification calculation formula.

[0031] The method for predicting the length of internal defects in continuously cast billets according to this application acquires the production data of the target billet and the estimated processing time under abnormal conditions, and combines this with the continuous casting speed adjustment process to quantitatively predict the change in the position of the solidification end of the continuously cast billet under abnormal conditions. Using a defect length prediction model based on solidification calculation formulas and the input production data and the first continuous casting speed V1, the prediction method of this application can accurately predict the possible length range of internal quality defects in the continuously cast billet when an abnormal speed reduction occurs, thereby providing a basis for the identification, marking, and subsequent process control of abnormal billets.

[0032] Therefore, by introducing an estimated processing time T and determining the first continuous casting speed V1 and its running time t2 at the initial stage of an anomaly, it is possible to predict the length range of internal quality defects under abnormal speed reduction conditions in continuous casting under continuous production conditions and abnormal operating conditions. This can effectively guide the internal quality control of the continuous casting billet, reduce quality risks, and achieve stable production and quality of the continuous casting billet.

[0033] Compared with existing technologies, this application can achieve advance prediction of internal quality risks in the continuous casting production process without relying on sampling and testing or sampling analysis of the billet. The prediction accuracy rate is over 98%, which helps to prevent abnormal billets from entering the subsequent rolling process, reduce the probability of quality accidents, and improve the stability and yield of the continuous casting production process.

[0034] In step S100 above, production data of the target billet is obtained, including the type of target billet, continuous casting speed V0, and thickness d of the target billet. The type of the target billet can be used to determine the solidification coefficient K in solidification calculations. Different types of billets correspond to different solidification characteristics.

[0035] The continuous casting speed V0 refers to the normal production speed before the anomaly occurs; for example, the continuous casting speed V0 can be 1-1.5 m / min. The billet thickness d is an important geometric parameter that determines the solidification heat transfer path and solidification rate, and can affect the solidified shell thickness e0 at the continuous casting speed V0. The billet thickness d can be 230 mm to 400 mm. For example, when the billet thickness d is 230 mm, the solidified shell thickness e0 is typically 115 mm.

[0036] The defect length prediction model refers to a mathematical-physical model that predicts the length of the billet with internal quality defects under abnormal working conditions by using the relationship between the thickness of the solidified billet shell and the length of the possible liquid core, based on the solidification law of continuous casting.

[0037] S200. Obtain the estimated processing time T under abnormal conditions, and based on the estimated processing time T, obtain the first continuous casting speed V1 under abnormal conditions and the running time t2 at the first continuous casting speed V1. Abnormal situations may include, but are not limited to, equipment malfunctions, process fluctuations, or adjustments to production schedules.

[0038] The first continuous casting speed V1 refers to the reduced continuous casting operating speed set under abnormal conditions to match the expected processing time T.

[0039] The running time t2 refers to the duration during which the continuous casting speed is stably maintained at V1, and is used to extend the residence time of the billet in the crystallizer and secondary cooling zone during abnormal handling.

[0040] When the continuous casting speed decreases from V0 to V1, the residence time of the billet in the crystallizer and secondary cooling zone increases, resulting in a thicker solidified shell and a corresponding shortening of the liquid core length. By mapping the change in solidified shell thickness to a change in liquid core length through geometric relationships, the migration of the solidification end position under abnormal operating conditions can be characterized.

[0041] In the continuous casting production process, the estimated processing time T required to maintain the abnormal operating state in response to equipment malfunctions, process adjustments, etc., is an important factor affecting the internal defects of the continuously cast billet.

[0042] Figure 2 This is a schematic diagram of the continuous casting structure showing the crystallizer position in one scenario embodiment provided in this application; from the diagram, the liquid core length L under the continuous casting speed V0 condition can be calculated or measured based on the crystallizer and the sector region.0， The core length L0 can be an arc shape; measuring or calculating the length of this arc shape gives the core length L0. For example, it can be measured... Figure 2 The length L0 of the liquid core of the molten steel or solidified billet shell in the A1 to A2 section is the length after the arc is unfolded or the length of the arc.

[0043] S302, based on the solidified shell thickness e0 and the liquid core length L0, and the formula... e0 / L0, we get the angle α; S303, according to the solidification calculation formula e=K The solidified shell thickness e2 during the time interval t0-t2 is obtained; where K is determined according to the type of the target billet. In this step, under abnormal operating conditions, the continuous casting speed changes, and the residence time of the billet in the crystallizer and the secondary cooling zone changes, thereby affecting the growth process of the solidified billet shell; based on the solidification calculation formula, the solidified billet shell thickness e2 can be calculated from the initial time t0 to the end time t2 of the abnormal stage.

[0044] S304, using the formula e0 / L0=(e0-e2) / (L0-L2), to obtain the liquid core length L2 of the first continuous casting speed V1; S305, based on the liquid core length L0 and the liquid core length L2, the length of the internal quality defect of the target billet under abnormal conditions is obtained as L0-L2.

[0045] The solidified shell thickness e0 refers to the thickness of the shell formed by the solidification of the outer layer of the billet under the continuous casting speed V0, and is a key parameter describing the degree of solidification.

[0046] The length of the liquid core L0 under normal continuous casting speed V0; the length of the liquid core L2 under the first continuous casting speed V1.

[0047] Angle α refers to the geometric angle formed by the thickness of the solidified billet shell and the length of the liquid core, used to describe the geometric relationship at the end of solidification. The solidification coefficient K is a solidification constant related to the type of billet and the characteristics of the steel grade, used to reflect the solidification rate characteristics of the material. For example, K can be 22-26 mm / (min). 1 / 2 ).

[0048] The solidification geometry angle α is used to characterize the geometric relationship between the solidified shell and the liquid core, reflecting the solidification expansion characteristics of the billet in the continuous casting direction. The solidification geometry angle α is determined by the ratio of the solidified shell thickness e0 to the liquid core length L0, e0 / L0, and is used for the geometric derivation of the liquid core length variation under different working conditions.

[0049] Therefore, by comparing the difference between L0 and L2, the magnitude of the backward or forward movement of the solidification end under abnormal working conditions is directly converted into the possible length of internal quality defects. By introducing solidification calculation formulas and geometric relationships, this invention can achieve quantitative prediction of defect length without relying on empirical judgment, thereby improving the accuracy and repeatability of prediction results.

[0050] Shortening the liquid core length from L0 to L2, within the range L0-L2, as the risk length for potential internal quality defects, can improve the billet yield and reduce the complexity of inspection, provided that billet production is continuous.

[0051] In some embodiments, in S200, the first continuous casting speed V1 under abnormal conditions and the running time t2 at the first continuous casting speed V1 are obtained based on the expected processing time T, specifically including: S201, in the event of an abnormality in continuous billet production, the production speed of the billet is adjusted, sequentially going through a deceleration stage, a constant speed stage, and a speed-up stage, wherein: During the deceleration phase, the steel strip decreases from the continuous casting speed V0 to the first continuous casting speed V1 with an acceleration a1, and the duration of the deceleration phase is t1. During this stage, by setting the acceleration a1, the continuous casting speed changes smoothly, avoiding any impact on the solidification state inside the billet.

[0052] During the constant speed phase, the running time t2 of the steel strip at the first continuous casting speed V1; During the constant speed stage, the billet runs stably at the first continuous casting speed V1 for a time of t2, which is used to extend the effective processing time of the billet during abnormal handling.

[0053] During the acceleration phase, the steel strip is accelerated from the first continuous casting speed V1 to the continuous casting speed V0 or the second continuous casting speed V2 at an acceleration a2, and the duration of the acceleration phase is t3. In S202, the running time t2 at the first continuous casting speed V1 is determined based on the initial running speed V0, the expected processing time T, and the durations t1 and t3.

[0054] In some embodiments, the duration t2 of the constant velocity phase satisfies the following relationship: V1t2=V0 0.5*a1t1 2 0.5*a2t3 2 .

[0055] In some embodiments, the duration t2 of the constant velocity phase satisfies the following relationship: t2 = t1 t3.

[0056] In the event of anomalies in continuous casting, it is usually necessary to reduce the continuous casting speed for a certain period of time to facilitate the handling of the anomalies, in order to ensure production continuity. For example, by decomposing the anomaly handling time T into three stages—deceleration, constant speed, and acceleration—it is possible to controllably adjust the continuous casting process and time without changing the billet thickness or the crystallizer structure.

[0057] Multiple operating stages make the change process of continuous casting speed controllable and calculable, thus providing a basis for accurately determining the constant speed stage operating time t2. Through three-stage speed adjustment, it not only meets the needs of abnormal handling, but also avoids the uncontrollable impact of sudden working conditions on the internal quality of the billet.

[0058] By accurately calculating the changes in the solidification end position during the three stages of decreasing speed, constant speed, and increasing speed, the length of the internal quality defects in the continuously cast billet under abnormal speed decrease can be effectively tracked and predicted, greatly improving the prediction accuracy.

[0059] Figure 3 This is a graph showing the change in speed versus time under abnormal conditions, provided in an embodiment of this application. Figure 4 This is a schematic diagram of the physical model at different continuous casting speeds provided in the embodiments of this application; from Figure 3 By observing the variations in continuous casting speed and time, we can understand the operating speed of the continuously cast billet under abnormal conditions; combined with... Figure 3 and Figure 4 This method uses a solidification physics model to quantitatively calculate the change in liquid core length, thereby accurately predicting the spatial distribution range of internal quality defects in the target billet under abnormal operating conditions. The method has clear physical meaning and a stable calculation process, effectively improving the reliability and feasibility of internal quality control in the continuous casting process.

[0060] In some embodiments, in S201, the duration t2 of the constant speed phase is determined according to the following relationship: .

[0061] Therefore, the duration t2 of the constant velocity phase can be calculated using this formula.

[0062] In some embodiments, V2 equals V0. In some embodiments, a1 equals a2.

[0063] In some embodiments, a1 is 0.15~0.25 m / min 2 Optionally, a1 can be 0.15 m / min 2 0.16 m / min 2 0.17 m / min 2 0.18 m / min 2 0.19 m / min 20.20 m / min 2 0.21 m / min 2 0.22 m / min 2 0.23 m / min 2 0.24 m / min 2 and 0.25 m / min 2 Any value or range of its composition in the range. This allows for a balance between the production quality of continuously cast billets and production efficiency.

[0064] In some embodiments, a2 is 0.15~0.25 m / min 2 Optionally, a1 can be 0.15 m / min 2 0.16 m / min 2 0.17 m / min 2 0.18 m / min 2 0.19 m / min 2 0.20 m / min 2 0.21 m / min 2 0.22 m / min 2 0.23 m / min 2 0.24 m / min 2 and 0.25 m / min 2 Any value or range of its composition in the range. This allows for a balance between the production quality of continuously cast billets and production efficiency.

[0065] In some embodiments, before obtaining the length of the internal quality defect of the target billet based on production data, the first continuous casting speed V1, and the defect length prediction model in S300, the prediction method further includes: S250, controlling L2 < L1 < L 0， L2 < L3 < L 0， Specifically, the liquid core length L1 during continuous casting is defined as follows: at duration t1, the liquid core length L3 is defined as follows: at duration t3, the liquid core length L3 is defined as follows. The defect length prediction model can predict the defect length of slabs with potential internal quality risks located in the liquid core under abnormal operating conditions. This guides the effective monitoring and isolation of slabs within this range, eliminating the risk of abnormal slabs being rolled into finished products and delivered to customers.

[0066] As an example, Figure 5 This is a schematic diagram of the liquid core length at different continuous casting speeds provided in the embodiments of this application; from Figure 5 As can be seen from this, by controlling L2 < L1 < L 0，L2 < L3 < L0 ensures that the change in liquid core length is continuous and controllable, avoiding non-physical or abnormal sudden changes, further improving the reliability of the prediction model, making the prediction results more consistent with the actual solidification law of continuous casting, and enhancing the applicability and stability of the method in the industrial field.

[0067] In some embodiments, in S250, the method for determining the liquid core length L1 includes: According to the solidification calculation formula e=K The solidified shell thickness e1 during the time interval t0-t1 is obtained. Using formula e0 / L0=(e0-e1) / (L0-L1), which gives the length L1 of the liquid core during the deceleration phase.

[0068] In some embodiments, in S250, the method for determining the liquid core length L3 of the cast billet includes: According to the solidification calculation formula e=K The solidified shell thickness e3 during the time interval t0-t3 is obtained. Using formula e0 / L0=(e0-e3) / (L0-L3), which gives the liquid core length L3 during the acceleration phase.

[0069] S300. Based on production data, the first continuous casting speed V1, and the defect length prediction model, the length of the internal quality defect of the target billet is obtained. The defect length prediction model is constructed based on the solidification calculation formula.

[0070] During the abnormal speed reduction process of continuous casting, the position of the solidification end changes, and the roll gap state and light reduction conditions in the sector section change accordingly. This makes the billet located within a specific liquid core length range more prone to internal quality defects such as center segregation, porosity, or shrinkage cavities. Therefore, based on production data, the first continuous casting speed V1, and the defect length prediction model, the length of internal quality defects in the billet can be predicted more accurately.

[0071] In some embodiments, in S300, the method for constructing the defect length prediction model includes: S301, based on the continuous casting speed V0 and thickness d, the solidified shell thickness e0 of the target billet and the liquid core length L0 under the continuous casting speed V0 condition are obtained. In this step, the liquid core length L0 refers to the length of the billet inside that is still in a liquid state under the continuous casting speed conditions.

[0072] Based on the billet thickness d, continuous casting speed V0, and billet type, combined with established solidification experience models or solidification calculation formulas, the solidified billet shell thickness e0 and liquid core length L0 corresponding to the target billet under continuous casting speed V0 conditions can be calculated.

[0073] To facilitate understanding of the method for predicting the length of internal defects in continuously cast billets in the embodiments of this application, the actual application process of this method is explained as follows: This embodiment provides a method for predicting the length of internal quality defects in continuously cast billets under abnormal speed reduction conditions, including the following steps: (1) Using the solidification calculation formula e=K The solidification coefficient is calculated as 26 mm / min 1 / 2 The calculated liquid core length L0 is 29.35 m, the solidified shell thickness e0 is 115 mm, and the solidification time t0 is 19.56 min under the condition of a pulling speed V0 of 1.4 m / min. Then, using the formula t1 = (V0 - V1) / a1, where V1 is the target velocity of 0.8 m / min and a1 is the deceleration acceleration of 0.25 m / min... 2， The calculated time t1 for the deceleration process is 6.8 minutes. Using the formula e1=K The calculated solidified shell thickness e1 during the time interval t0-t1 is 92.87 mm. Then, using the formula... e0 / L0=(e0-e1) / (L0-L1), the calculated core length L1 under the deceleration condition is 23.7 m.

[0074] (2) The running time of the first continuous casting speed V1 is 0.8 m / min, and t2 is 16.8 min. Using the formula e2=K The calculated solidified shell thickness e2 during the time interval t0-t2 is 43.19 mm. Then, using the formula... e0 / L0=(e0-e2) / (L0-L2), the core length L2 at the first continuous casting speed V1 is calculated to be 11.02 m.

[0075] (3) Using the formula t3=(V2-V1) / a2, the time t3 taken during the acceleration process is calculated to be 17.3 min, where a2 is the deceleration acceleration of 0.25 m / min. 2 The target velocity of V2 is 1.3 m / min. Then, using the formula e3=K... The calculated solidified shell thickness e3 during the time interval t0-t3 is 39.08 mm. Then, using the formula... e0 / L0=(e0-e3) / (L0-L3), the liquid core length L3 during the acceleration process is calculated to be 25.43 m.

[0076] (4) Calculate the forward movement of the solidification end position during the acceleration process. S4: Based on L0, L1, L2 and L3 calculated by S1-S3 above, predict the length range of internal quality defects in the continuously cast billet under abnormal deceleration conditions, that is, 27.39~11.02m in the continuous casting metallurgical length. In other words, the billet with the predicted internal quality risk is located in the liquid core length between 27.39 and 11.02m. The actual length of the billet with quality problems corresponds to 17m, which is within the predicted length range of L0-L2.

[0077] Through the above operations, the model predicting the length range of internal quality defects in continuously cast billets under abnormal speed reduction conditions can effectively track and predict the corresponding lengths of internal quality defects in continuously cast billets under abnormal speed reduction conditions with 100% accuracy. As an example, Figure 6 This is an external view of a continuously cast billet with internal defects provided in an embodiment of this application; Figure 7 This is an external view of a continuously cast billet with no internal defects, provided in an embodiment of this application; through Figure 6 and Figure 7 By observing the appearance of a portion of the continuously cast billet and marking the corresponding positions, the internal quality defects of the next continuously cast billet, i.e., the corresponding L0-L2, can be removed. Thus, while taking into account production efficiency and continuous production, the internal quality defects of the continuously cast billet can be accurately predicted and located, and then removed.

[0078] In summary, the prediction method of this application embodiment has the following beneficial technical effects: 1. The prediction method of this application embodiment is based on long-term tracking of the historical data characteristics of continuously cast billets, and the resulting prediction method closely matches the actual situation of internal defects in the billets. 2. Under different abnormal working conditions, the corresponding abnormal working conditions in the production process of continuously cast billets are different, and the expected processing time is different. The V1 involved in this prediction method and the expected processing time T can be modified at any time according to the changes in abnormal working conditions, making the rules more closely match the actual abnormal production situation.

[0079] Based on the method for predicting the length of internal defects in continuously cast billets provided in the above embodiments, this application also provides a specific implementation of a device for predicting the length of internal defects in continuously cast billets. Please refer to the following embodiments.

[0080] Figure 8 This is a schematic diagram of the structure of the device for predicting the length of internal defects in continuously cast billets provided in the embodiments of this application; as shown... Figure 8 As shown, the prediction device 800 for the length of internal defects in continuously cast billets provided in this application embodiment may include the following modules: acquisition module 801, determination module 802, and prediction module 803.

[0081] The acquisition module 801 is used to acquire the production data of the target billet, including the type of the target billet, the continuous casting speed V0, and the thickness d of the target billet. The determination module 802 is used to obtain the estimated processing time T under abnormal conditions, and based on the estimated processing time T, to obtain the first continuous casting speed V1 under abnormal conditions and the running time t2 at the first continuous casting speed V1. The prediction module 803 is used to obtain the length of the internal quality defects of the target billet based on production data, the first continuous casting speed V1 and the defect length prediction model.

[0082] In some embodiments, the method for constructing the defect length prediction model in the prediction module 803 includes: The preset submodule is used to obtain the solidified shell thickness e0 of the target billet and the liquid core length L0 under the continuous casting speed V0 based on the continuous casting speed V0 and the thickness d. The calculation submodule is used to calculate the solidified shell thickness e0, the liquid core length L0, and the formula. e0 / L0, we get the angle α; The blank thickness determination module is used to calculate the thickness based on the solidification formula e=K. The solidified shell thickness e2 during the time interval t0-t2 is obtained; where K is determined according to the type of the target billet. The liquid core length L2 determination module is used to determine the liquid core length using the formula e0 / L0=(e0-e2) / (L0-L2), to obtain the liquid core length L2 of the first continuous casting speed V1; The calculation output module is used to obtain the length of the internal quality defect of the target billet under abnormal conditions as L0-L2 based on the liquid core length L0 and the liquid core length L2.

[0083] In some embodiments, the determining module 802 specifically includes: The speed control module is used to adjust the production speed of the billet in case of abnormal continuous production, sequentially going through a deceleration stage, a constant speed stage, and a speed-up stage, wherein: During the deceleration phase, the steel belt decreases from velocity V0 to velocity V1 with acceleration a1, and the duration of the deceleration phase is t1. During the constant speed phase, the running time t2 of the steel strip at the first continuous casting speed V1; During the acceleration phase, the steel strip accelerates from speed V1 to continuous casting speed V0 or V2 with an acceleration a2, and the duration of the acceleration phase is t3. The time calculation module is used to determine the running time t2 at the first continuous casting speed V1 based on the initial running speed V0, the expected processing time T, and the durations t1 and t3.

[0084] In some embodiments, before the prediction module 803, the prediction device 800 further includes: a control module for controlling L2 < L1 < L 0， L2 < L3 < L0， Among them, the liquid core length L1 during continuous casting is measured at duration t1; and the liquid core length L3 during continuous casting is measured at duration t3.

[0085] In some embodiments, the prediction device 800 further includes: a liquid core length L1 determination module, used to determine the liquid core length L1: The module for determining the solidified shell thickness e1 is used to calculate the thickness based on the solidification formula e=K. The solidified shell thickness e1 during the time interval t0-t1 is obtained. The liquid core length L1 calculation module is used to calculate the liquid core length using the formula e0 / L0=(e0-e1) / (L0-L1), which gives the length L1 of the liquid core during the deceleration phase.

[0086] In some embodiments, the prediction device 800 further includes: a liquid core length L3 determination module, used to determine the liquid core length L3, specifically including: The solidified shell thickness e3 determination module is used to calculate the solidification thickness based on the solidification formula e=K. The solidified shell thickness e3 during the time interval t0-t3 is obtained. The liquid core length L3 calculation module is used to calculate the liquid core length using the formula. e0 / L0=(e0-e3) / (L0-L3), which gives the liquid core length L3 during the acceleration phase.

[0087] Figure 9 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application is shown. The electronic device may include a processor 901 and a memory 902 storing computer program instructions.

[0088] Specifically, the processor 901 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0089] Memory 902 may include mass storage for data or instructions. For example, and not limitingly, memory 902 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 902 may include removable or non-removable (or fixed) media. Where appropriate, memory 902 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 902 is non-volatile solid-state memory.

[0090] In a particular embodiment, memory 902 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Thus, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the prediction method according to one aspect of this disclosure.

[0091] The processor 901 reads and executes computer program instructions stored in the memory 902 to implement any of the methods for predicting the length of internal defects in continuously cast billets in the above embodiments.

[0092] In one example, the electronic device may also include a communication interface 903 and a bus 910. Wherein, as... Figure 9 As shown, the processor 901, memory 902, and communication interface 903 are connected via bus 910 and communicate with each other. The communication interface 903 is mainly used to realize communication between various modules, devices, units, and / or equipment in the embodiments of this application.

[0093] Bus 910 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 910 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0094] This electronic device can execute the method for predicting the length of internal defects in continuously cast billets as described in the embodiments of this application, thereby achieving a combination of... Figure 1 and Figure 8 The method and apparatus described herein are for predicting the length of internal defects in continuously cast billets.

[0095] Furthermore, in conjunction with the method for predicting the length of internal defects in continuously cast billets in the above embodiments, this application embodiment can provide a computer-readable storage medium for implementation. This computer-readable storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the methods for predicting the length of internal defects in continuously cast billets in the above embodiments.

[0096] This application also provides a computer program product, including a computer program that, when executed, implements any of the methods for predicting the length of internal defects in continuously cast billets described in the above embodiments.

[0097] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known prediction methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the prediction method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0098] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0099] It should also be noted that the exemplary embodiments mentioned in this application describe some prediction methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0100] The foregoing flowcharts and / or block diagrams of prediction methods, apparatus (systems), and computer program products according to embodiments of the present disclosure have described various aspects of the present disclosure. It should be understood that each block in the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to create a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowcharts and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0101] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing prediction method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for predicting the length of internal defects in continuously cast billets, characterized in that, include: Obtain production data for the target billet, including the type of the target billet, the continuous casting speed V0, and the thickness d of the target billet; Obtain the estimated processing time T under abnormal conditions, and based on the estimated processing time T, obtain the first continuous casting speed V1 under the abnormal conditions and the running time t2 at the first continuous casting speed V1. Based on the production data, the first continuous casting speed V1, and the defect length prediction model, the length of the internal quality defect of the target billet is obtained, wherein the defect length prediction model is constructed based on the solidification calculation formula.

2. The prediction method according to claim 1, characterized in that, The method for constructing the defect length prediction model includes: Based on the continuous casting speed V0 and the thickness d, the solidified shell thickness e0 of the target billet and the liquid core length L0 under the continuous casting speed V0 condition are obtained. Based on the solidified shell thickness e0 and the liquid core length L0, and the formula... e0 / L0, we get the angle α; According to the solidification calculation formula e=K The solidified shell thickness e2 during the time interval t0-t2 is obtained; where K is determined according to the type of the target billet. Using formula e0 / L0=(e0-e2) / (L0-L2), to obtain the liquid core length L2 under the condition of the first continuous casting speed V1; Based on the liquid core length L0 and the liquid core length L2, the length of the internal quality defect of the target billet under the abnormal condition is obtained as L0-L2.

3. The prediction method according to claim 1, characterized in that, The step of obtaining the first continuous casting speed V1 under the abnormal condition and the running time t2 at the first continuous casting speed V1 based on the expected processing time T includes: In the event of abnormal continuous billet production, the production speed of the billet is adjusted, sequentially going through a deceleration stage, a constant speed stage, and a speed-up stage, wherein: During the deceleration phase, the steel strip decreases from the continuous casting speed V0 to the first continuous casting speed V1 with an acceleration a1, and the duration of the deceleration phase is t1. During the constant speed phase, the running time t2 of the steel strip at the first continuous casting speed V1; During the acceleration phase, the steel strip is accelerated from the first continuous casting speed V1 to the continuous casting speed V0 or the second continuous casting speed V2 at an acceleration a2, and the duration of the acceleration phase is t3. The running time t2 at the first continuous casting speed V1 is determined based on the continuous casting speed V0, the expected processing time T, the duration t1, and the duration t3.

4. The prediction method according to claim 3, characterized in that, The running time t2 of the constant speed phase is determined according to the following relationship: 。 5. The prediction method according to claim 3 or 4, characterized in that, V2 equals V0, and / or a1 is 0.15~0.25 m / min 2 ; and / or, a2 is 0.15~0.25 m / min 2 .

6. The prediction method according to claim 3 or 4, characterized in that, Before obtaining the length of the internal quality defect of the target billet based on the production data, the first continuous casting speed V1, and the defect length prediction model, the prediction method further includes: controlling L2 < L1 < L 0， L2 < L3 < L 0， Among them, the liquid core length L1 during continuous casting is measured at duration t1; and the liquid core length L3 during continuous casting is measured at duration t3.

7. The prediction method according to claim 6, characterized in that, The method for determining the liquid core length L1 includes: According to the solidification calculation formula e=K The solidified shell thickness e1 during the time interval t0-t1 is obtained. Using formula e0 / L0=(e0-e1) / (L0-L1), to obtain the liquid core length L1 during the deceleration stage.

8. The prediction method according to claim 6, characterized in that, The methods for determining the liquid core length L3 of the cast billet include: According to the solidification calculation formula e=K The solidified shell thickness e3 during the time interval t0-t3 is obtained. Using formula e0 / L0=(e0-e3) / (L0-L3), which gives the liquid core length L3 during the acceleration phase.

9. A device for predicting the length of internal defects in continuously cast billets, characterized in that, The device includes: The acquisition module is used to acquire production data of the target billet, including the type of the target billet, the continuous casting speed V0, and the thickness d of the target billet. The determination module is used to obtain the estimated processing time T under abnormal conditions, and based on the estimated processing time T, to obtain the first continuous casting speed V1 under the abnormal conditions and the running time t2 at the first continuous casting speed V1. The prediction module is used to obtain the length of the internal quality defects of the target billet based on the production data, the first continuous casting speed V1 and the defect length prediction model, wherein the defect length prediction model is constructed based on the solidification calculation formula.

10. An electronic device, characterized in that, The device includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the method for predicting the length of internal defects in continuously cast billets as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the method for predicting the length of internal defects in continuously cast billets as described in any one of claims 1-8.

12. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the method for predicting the length of internal defects in continuously cast billets as described in any one of claims 1-8.

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