A method for early warning and maintenance decision-making regarding nozzle clogging in continuous casting

Abstract

This invention discloses a method for early warning and maintenance decision-making regarding nozzle clogging in continuous casting based on flow field simulation. First, nozzle clogging is quantified as a stepwise reduction in the equivalent inner diameter, and a series of geometric models are established. Second, CFD simulations are performed on these models to obtain the crystallizer flow field under different clogging levels. Then, key flow field indicators are extracted and their variation with the inner diameter is analyzed to determine the critical inflection point of flow field deterioration. Finally, the inner diameter value corresponding to this inflection point is set as the early warning threshold to guide nozzle condition assessment and preventative maintenance in actual production. This invention realizes the transformation of nozzle maintenance from "timed inspection" to "on-demand early warning," improving the intelligence level and quality stability of continuous casting production.

Description

Technical Field

[0001] This invention relates to the field of continuous casting equipment condition monitoring and process maintenance in iron and steel metallurgy, specifically to a method for early warning and maintenance decision-making regarding nozzle clogging in continuous casting. Background Technology

[0002] During continuous casting, nodule formation (deposition of inclusions such as Al2O3) on the inner wall of the nozzle is a common phenomenon. Nodule formation leads to a reduction in the actual inner diameter and shape of the nozzle, which significantly worsens the flow field of molten steel in the mold. This manifests as increased surface fluctuations, unreasonable impact depth, and increased risk of slag entrapment, ultimately affecting the quality of the cast billet and production safety.

[0003] Currently, monitoring of nozzle formation mainly relies on: 1. Experience-based timed replacement: Replacement is based on fixed pouring times or molten steel volumes, lacking specificity. Replacing too early may result in waste, while replacing too late may lead to quality issues.

[0004] 2. Indirect judgment by humans: Indirect inference is made by observing fluctuations in pulling speed and liquid surface, which has a lag and subjectivity and cannot provide early warning before the flow field deteriorates substantially.

[0005] 3. Offline measurement: Measurements are taken after disassembly following production shutdown, making online evaluation impossible.

[0006] Current technology lacks an effective means to quantitatively assess the impact of nozzle nodules on the internal flow field during production and to scientifically predict maintenance timing. Establishing a quantitative relationship between nodule size, flow field state, and quality risk, and using this relationship to guide preventative maintenance, is a pressing issue in this field.

[0007] This invention aims to overcome the shortcomings of existing technologies and provide a method for early warning and maintenance decision-making regarding nozzle clogging in continuous casting based on flow field simulation. This method quantifies nozzle clogging as a change in geometric parameters, establishes a quantitative mapping relationship between the degree of clogging and the degree of flow field deterioration through a series of simulations, identifies key inflection points in flow field deterioration, and sets the clogging state corresponding to these inflection points as an early warning threshold, thereby achieving online prediction of nozzle conditions and scientific maintenance decisions. Summary of the Invention

[0008] The purpose of this invention is to address the above-mentioned problems by providing a method for early warning and maintenance decision-making regarding nodule formation in continuous casting nozzles.

[0009] The objective of this invention is achieved as follows: A method for early warning and maintenance decision-making regarding nozzle clogging in continuous casting, comprising the following steps: Step 1: Defining a series model for nozzle clogging evolution: Abstracting nozzle clogging as a continuous decrease in the nozzle inner diameter, based on the design inner diameter D0 70 mm, defining a set of equivalent inner diameter values ​​D that decrease in gradient under the condition of no clogging. i (i=1,2,...n), this series Di This represents different stages of nodule formation, from mild to severe, for each D. i Establish the corresponding three-dimensional parametric geometric model of the nozzle and crystallizer; Step 2: Perform a series of flow field simulations: for each equivalent inner diameter D defined in Step 1 i The model is used for numerical simulation calculations under the same process conditions to obtain a stable molten steel flow field in the crystallizer under various nodule formation levels; Step 3: Extract flow field characteristic indicators strongly related to quality: For each simulation result, extract 3-5 quantifiable flow field characteristic indicator values ​​F that are directly related to the quality of the cast billet. i These indicators include, but are not limited to: F1: the maximum flow velocity or velocity variation at the free surface of the crystallizer; F2: the pressure difference generated by fluctuations at the free surface of the crystallizer; F3: the depth of the jet impact point from the meniscus; F4: the difference ratio of the intensity of the upper recirculation zones on the left and right sides of the crystallizer; Step 4: Determine the critical inflection point of flow field deterioration: Analyze the curve of the flow field characteristic index value Fⱼ as the equivalent inner diameter Dᵢ decreases, and identify the critical inner diameter Dc corresponding to the sudden change in the index value in the curve; Step 5: Establish early warning and decision-making rules: Set the critical inner diameter Dc determined in Step 4 as the early warning for nozzle maintenance. Thresholds and the following decision-making rules are established: Online monitoring and evaluation: In actual production, the current equivalent inner diameter Dc of the nozzle is estimated in real time or periodically through model prediction, empirical formula calculation based on casting time / steel grade, or image processing technology. Early warning trigger: When Dc≤Dc+Δ, where Δ is a safety margin of 1-2mm, the alarm device issues an early warning signal, indicating that the nozzle nodule is approaching the critical state that leads to the deterioration of the flow field. Maintenance recommendations: Schedule planned inspections, i.e., inspect, clean, or replace the nozzle once every 120t of molten steel is produced, to avoid continuing production when the flow field has deteriorated.

[0010] The beneficial effects of this invention are: 1. From experience to science: It transforms the maintenance of the water inlet from relying on fixed cycles or manual experience to scientific decision-making based on quantitative assessment of the flow field state, thus realizing predictive maintenance.

[0011] 2. Intuitive quantitative correlation: A clear and quantitative chain of "nodule size (Dᵢ) → flow field index (Fⱼ) → quality risk" has been established, making the basis for maintenance more objective and reliable.

[0012] 3. Proactive early warning: It can issue an early warning before the flow field deteriorates substantially and affects product quality, leaving a time window for arranging non-urgent planned maintenance and avoiding unplanned downtime and quality loss.

[0013] 4. High flexibility: The method can be customized for different steel grades, casting speeds, and nozzle types, and establish a dedicated early warning threshold library to adapt to changing field conditions. Attached Figure Description

[0014] The present invention will now be further described with reference to the accompanying drawings.

[0015] Figure 1 This is a diagram showing the pressure difference at the free liquid level in the crystallizer of this invention.

[0016] Explanation: As the inner diameter of the nozzle decreases (i.e., nodulation occurs), the pressure difference at the free liquid surface in the crystallizer gradually increases, resulting in violent fluctuations in the liquid surface. When the inner diameter of the nozzle decreases to 54 mm, the pressure difference changes abruptly, causing violent fluctuations in the liquid surface. Detailed Implementation

[0017] This method aims to solve the industry problem of difficulty in quantifying and assessing the state of nozzle nodules and the inability to provide early warnings of their impact on the flow field. This solution aims to achieve a technical system of "nodule quantification - simulation mapping - inflection point early warning": 1. Abstracting nodules into a stepwise reduction of the equivalent inner diameter of the nozzle, constructing a series of three-dimensional geometric models; 2. Employing computational fluid dynamics methods to accurately obtain key indicators such as surface turbulent kinetic energy and free surface pressure difference; 3. Identifying critical inflection points of flow field deterioration through data analysis, setting the corresponding nodule size as an early warning threshold, and combining this with production data models to achieve real-time status assessment and maintenance decision triggering.

[0018] Innovation points: 1. Mechanism innovation: For the first time, a complete quantitative mapping model of "nodule size → flow field characteristics → quality risk" is established, which directly links the difficult-to-observe internal nodules with quantifiable flow field indicators.

[0019] 2. Methodological innovation: A series of comparative simulations are used to replace single-point analysis. The warning trigger point is determined by identifying the abrupt inflection point of the flow field index (instead of a simple threshold), resulting in higher warning accuracy.

[0020] 3. Application Innovation: Transform numerical simulation results into executable maintenance decision rules, realizing a transformation of the maintenance mode from "periodic replacement" to "condition-based early warning".

[0021] 4. Core method features: The method abstracts nozzle nodules as a continuous change in equivalent inner diameter and performs comparative flow field simulations on a series of decreasing equivalent inner diameters to establish a quantitative relationship between the degree of nodules and flow field indicators.

[0022] 5. Inflection Point Judgment Characteristics: This step involves analyzing the curves of flow field indicators changing with the equivalent inner diameter to identify the critical points (deterioration inflection points) where the indicators undergo sudden changes or exceed limits, and using the nodulation status corresponding to these critical points as the basis for judgment.

[0023] 6. Early warning application characteristics: The critical inner diameter (D_critical) determined by the above simulation is set as the early warning threshold and used to trigger early warning or maintenance decisions for the sprue status in actual production.

[0024] This method can: issue early warnings 1-2 casting cycles before substantial deterioration of the flow field, leaving a window for planned maintenance; and make nozzle replacement decisions based on flow field status data, avoiding excessive or insufficient maintenance, which is expected to reduce nozzle consumption costs by 15%-25%. This system provides key technical support for the intelligent upgrading of continuous casting production.

[0025] A method for early warning and maintenance decision-making regarding nozzle clogging in continuous casting based on flow field simulation includes the following steps: S1. Define a series of models for nozzle clogging evolution: Abstract nozzle clogging as a continuous decrease in the effective flow inner diameter of the nozzle. Based on the design inner diameter D0 (70mm, no clogging), define a set of equivalent inner diameter values ​​D that decrease in a gradient. i (i=1,2,...n), for example, D i =[70, 66, 62, 58, 54, 50] mm. This series D i This represents different stages of nodulation, from mild to severe. For each Dᵢ, a corresponding three-dimensional parametric geometric model of the nozzle and crystallizer is established.

[0026] S2. Perform a series of flow field simulations: For each equivalent inner diameter Dᵢ model defined in S1, perform numerical simulation calculations under the same process conditions (such as casting speed, immersion depth, and superheat). The simulation calculations obtain the stable molten steel flow field inside the crystallizer under various nodulation levels.

[0027] S3. Extract flow field characteristic indices strongly correlated with quality: For each simulation result, extract one or more quantifiable flow field characteristic index values ​​F that are directly related to the quality of the cast billet. i These indicators include, but are not limited to: - F1: Maximum flow velocity or flow velocity variation at the free surface of the crystallizer. - F2: Pressure difference generated by fluctuations at the free surface of the crystallizer. - F3: Depth of the jet impact point from the meniscus. - F4: The ratio of the intensity difference between the upper recirculation zones on the left and right sides of the crystallizer.

[0028] S4. Determine the critical inflection point of flow field deterioration: Analyze the characteristic index value F of the flow field. i With equivalent inner diameter D i The curve shows a decrease in the critical inner diameter Dc. This involves identifying the points in the curve where the index value abruptly changes or exceeds a certain empirical safety limit. While empirical safety limits are largely derived from field experience, this paper focuses more on identifying points where the index value abruptly changes on the curve.

[0029] S5. Establish Early Warning and Decision-Making Rules: Set the critical inner diameter Dc determined in step S4 as the early warning threshold for nozzle maintenance. Develop the following decision-making rules: - Online Monitoring and Evaluation: In actual production, estimate the current equivalent inner diameter Dc of the nozzle in real time or periodically using techniques such as model prediction, empirical formulas based on casting time / steel grade, or image processing. - Early Warning Trigger: When Dc ≤ Dc + Δ (Δ is a safety margin, e.g., 1-2 mm), the system issues an early warning signal, indicating that nozzle nodule formation is approaching a critical state that leads to flow field deterioration. - Maintenance Recommendations: The early warning signal can be linked to the maintenance system, recommending planned inspection, cleaning, or replacement of the nozzle to avoid continued production when the flow field has deteriorated. Example 1

[0030] Taking the sprue of a slab continuous casting machine (1500×200) as an example: S1 Implementation: Design inner diameter D0 = 70mm. Define the nodule series model: D i =[70, 66, 62, 58, 54, 50] mm. Models of these six different inner diameter nozzle-crystallizer systems were created using 3D modeling software.

[0031] S2 implementation: The pulling speed was set to 1.15 m / min, and the immersion depth to 160 mm. Using the same mesh generation strategy, boundary condition parameters, and turbulence model, CFD steady-state simulation calculations were performed on the six models respectively.

[0032] S3 Implementation: Extract the average turbulent kinetic energy (TKE) of the liquid surface unit 50mm from the narrow edge of the crystallizer under each operating condition as the core indicator F. i .

[0033] S4 Implementation: Drawing F i Follow D i The changing curve. Finding: When D... i When TKE is ≥58mm, the growth is gradual (<0.002m² / s²); when D i When the thickness decreased from 58 mm to 54 mm, the TKE increased sharply to 0.005 m² / s², an increase of over 150%. Therefore, the deterioration inflection point was determined to be Dc > 54 mm.

[0034] S5 Implementation: A warning threshold is set: Dw = Dc + 2mm > 56mm. During production, based on historical data of the steel cast from this nozzle, a nodule formation rate model is established: for each heat of steel cast (200 tons), the equivalent inner diameter decreases by approximately 2mm. When the system has cumulatively cast 1400 tons (reducing from 70mm to 56mm), the warning system is automatically triggered, indicating "Nodule formation is approaching a critical state; inspection or replacement is recommended before the next casting cycle," thus avoiding potential quality problems caused by flow field deterioration.

[0035] The above description is only a specific embodiment of the present invention, but the structural features protected by the present invention are not limited thereto. Any changes or modifications made by those skilled in the art within the scope of the present invention are covered by the patent scope of the present invention.

Claims

1. A method for early warning and maintenance decision-making regarding nozzle clogging in continuous casting, characterized in that: Includes the following steps: Step 1: Define the nodule evolution series model: Abstract the nodule formation at the sprue as a continuous decrease in the inner diameter of the sprue. Based on the design inner diameter D0 70 mm, and the case without nodule formation, define a set of equivalent inner diameter values ​​D that decrease in a gradient. i (i=1,2,...n), this series D i This represents different stages of nodule formation, from mild to severe, for each D. i Establish corresponding three-dimensional parametric geometric models of the water inlet and crystallizer; Step 2: Perform a series of flow field simulations: For each equivalent inner diameter D defined in Step 1 i The model was used to perform numerical simulation calculations under the same process conditions, and the simulation calculations obtained a stable molten steel flow field in the crystallizer under various degrees of nodulation. Step 3: Extract flow field characteristic indices strongly correlated with quality: For each simulation result, extract 3-5 quantifiable flow field characteristic index values ​​F that are directly related to the quality of the cast billet. i These indicators include, but are not limited to: F1: the maximum flow velocity or flow velocity variation at the free surface of the crystallizer; F2: the pressure difference generated by fluctuations at the free surface of the crystallizer; F3: the depth of the jet impact point from the meniscus; and F4: the ratio of the intensity difference between the upper recirculation zones on the left and right sides of the crystallizer. Step 4: Determine the critical inflection point of flow field deterioration: Analyze the curve of the flow field characteristic index value Fⱼ as the equivalent inner diameter Dᵢ decreases, and identify the critical inner diameter Dc corresponding to the sudden change of the index value in the curve; Step 5: Establish Early Warning and Decision-Making Rules: Set the critical inner diameter Dc determined in Step 4 as the early warning threshold for nozzle maintenance, and formulate the following decision-making rules: Online Monitoring and Evaluation: In actual production, estimate the current equivalent inner diameter Dc of the nozzle in real time or periodically through model prediction, empirical formula calculation based on casting time / steel grade, or image processing technology. Early Warning Trigger: When Dc≤Dc+Δ, where Δ is a safety margin of 1-2mm, the alarm device issues an early warning signal, indicating that nozzle nodule formation is approaching the critical state that leads to flow field deterioration. Maintenance Recommendation: Arrange planned inspections, i.e., inspect, clean, or replace the nozzle once every 120t of molten steel produced, to avoid continuing production when the flow field has deteriorated.

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