Slab Quality Research Articles

Prediction of slab surface longitudinal crack based on resampling and the Bayesian optimisation of LightGBM

Longitudinal crack is a typical surface defect for slab of steel. Accurate prediction of longitudinal crack is of great significance to improve slab quality. However, in actual production, the quantity distribution of normal and longitudinally cracked slabs is extremely unbalanced, which brings great challenges to the subsequent modeling and prediction. To solve the above problems, this paper proposes a prediction method for the longitudinal crack under the condition of data imbalance. Firstly, multiple sampling methods (SMOTE, BorderlineSMOTE, SMOTE-ENN and SMOTE-Tomk) were used to construct feature data sets respectively to alleviate the problem of data imbalance. Then, based on the data sets after sampling processing, the prediction models of the longitudinal crack were constructed by using Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), XGBoost and LightGBM as classification algorithms. The models’ hyperparameters were determined by Bayesian optimisation and the optimal classification algorithm was selected according to the evaluation metrics. Meantime, SHapley Additive exPlanations (SHAP) was used to analyse the model and verify the influence of input parameters on the model output. The results show that, compared with other models, the combined model of SMOTE sampling and LightGBM classification algorithm can better deal with the problem of imbalanced data for prediction of the longitudinal crack. The Recall of normal and longitudinally cracked slabs are 90.57% and 84.62%, respectively, false alarm rate is 9.44% and AUC is 0.93. At the same time, the training time of this model is about 0.15 s, and prediction time is less than 0.01 s. The time consumed in each stage is significantly shorter than other models. It shows obvious advantages and provides a reliable method for predicting the longitudinal crack.

Comparison of transformation behavior of the peritectic steels with different carbon content and its correlation to the slab quality during solidification

In order to investigate the phase transformation behaviour of peritectic steels, we devise an integrated facility for X-ray transmission imaging combined with Laue diffraction analysis and precise temperature control. This integrated facility can measure the temperature at which the delta phase transforms into the gamma phase during solidification with continuous cooling. The investigation of four alloys with different carbon content reveals the dependence of carbon content on the minimum undercooling required for gamma phase formation. As carbon content increases, the amount of undercooling for the peritectic transformation decreases, and the gamma phase onset temperature necessarily increases. X-ray transmission images, which present the growing dendrites and moving delta-to-gamma interface, confirm that the peritectic reaction is likely to occur with high carbon content, leading to the gamma phase formation before the end of solidification.On the contrary, the low carbon content suppresses the gamma phase formation, and the solid delta and liquid phase exist under equilibrium peritectic temperature. Once after the gamma phase nucleation, the phase change occurs rapidly with increasing undercooling. The delay in gamma phase formation results in massive phase transition and rapid change of interface velocity with a slight variation of undercooling. The fast kinetic of solid phase transformation is associated with a corresponding increase of internal stress, leading to the degradation of slab quality.

Intelligent Inspection Method for Rebar Installation Quality of Reinforced Concrete Slab Based on Point Cloud Processing and Semantic Segmentation

The rebar installation quality significantly impacts the safety and durability of reinforced concrete (RC) structures. Traditional manual inspection is time-consuming, inefficient, and highly subjective. In order to solve this problem, this study uses a depth camera and aims to develop an intelligent inspection method for the rebar installation quality of an RC slab. The Random Sample Consensus (RANSAC) method is used to extract point cloud data for the bottom formwork, the upper and lower rebar lattices, and individual rebars. These data are utilized to measure the concrete cover thickness, the distance between the upper and lower rebar lattices, and the spacing between rebars in the RC slab. This paper introduces the concept of the “diameter calculation region” and combines point cloud semantic information with rebar segmentation mask information through the relationship between pixel coordinates and camera coordinates to measure the nominal diameter of the rebar. The verification results indicate that the maximum deviations for the concrete cover thickness, the distance between the upper and lower rebar lattices, and the spacing of the double-layer bidirectional rebar in the RC slab are 0.41 mm, 1.32 mm, and 5 mm, respectively. The accuracy of the nominal rebar diameter measurement reaches 98.4%, demonstrating high precision and applicability for quality inspection during the actual construction stage. Overall, this study integrates computer vision into traditional civil engineering research, utilizing depth cameras to acquire point cloud data and color results. It replaces inefficient manual inspection methods with an intelligent and efficient approach, addressing the challenge of detecting double-layer reinforcement. This has significant implications for practical engineering applications and the development of intelligent engineering monitoring systems.

Control of Instantaneous Abnormal Mold Level Fluctuation in Slab Continuous Casting Mold Based on Bidirectional Long Short‐Term Memory Model

The instantaneous abnormal mold level fluctuation (IAMLF) has significant harmful effects on slab quality. This article proposes a prediction and control method for IAMLF. First, the data processed by difference method is used for the IAMLF prediction and stopper‐rod position prediction. Then, the bidirectional long short‐term memory (BI‐LSTM) is introduced to predict the IAMLF; the corresponding stopper‐rod position is predicted according to the mold level prediction result. BI‐LSTM can predict the IAMLF with the mean absolute error of 1.52 mm and the false alarm rate of 1.8%, and also performs well in predicting the stopper‐rod position with a mean absolute error of only 1.92 mm. Furthermore, the two prediction models are combined to form a closed loop, where the mold level fluctuation is predicted according to the industrial data processed by data difference method, and the stopper‐rod position is adjusted in advance to eliminate IAMLF. Finally, the fuzzy proportional‐integral‐derivative (PID) controller is used to control mold level based on the mold level and stopper‐rod position prediction results. The prediction accuracy of IAMLF reaches 98.4%, and the present proposed fuzzy PID controller can effectively prevent the occurrence of IAMLF with a success rate of 95.6%.

Application of crystallization additivity principle in continuous casting mould flux

Testing the isothermal crystallization of mould fluxes poses challenges due to their high critical cooling rates. As a result, isothermal crystallization can be estimated from non-isothermal crystallization using the principle of crystalline additivity. However, the relationship between the TTT (Temperature Time Transformation) and CCT (Continuous Cooling Transformation) curves for volatile mould fluxes remains chaotic. This research introduces precise measurements of both isothermal and non-isothermal crystallization of volatile mould fluxes under conditions that suppressed fluoride volatilization for the first time. The CCT curves derived using the additive principle closely match the experimentally observed patterns, with only minor discrepancies, thereby validating the effectiveness of the additive principle in slag studies. Mould flux BA3 displays a double C-shaped TTT curve, where the high-temperature and low-temperature C-shapes represent distinct crystalline phases. If the computed CCT curve, generated by combining the incubation times of the two C-shaped crystallizations from the TTT curve, significantly diverges from the measured value at temperatures below the partition temperature, segmenting the CCT curve calculations based on high-temperature and low-temperature C-shape data from the TTT curve leads to calculated values that align with experimental results. The study enhances understanding of mould flux crystallization kinetics, crucial for improving the surface quality of continuous casting slab.

Analysis of Longitudinal Cracking and Mold Flux Optimization in High-Speed Continuous Casting of Hyper-Peritectic Steel Thin Slabs

Longitudinal crack defects are a frequent occurrence on the surface of thin slabs during the high-speed continuous casting process. Therefore, this study undertakes a detailed analysis of the solidification characteristics of hyper-peritectic steel thin slabs. By establishing a three-dimensional heat transfer numerical model of the thin slab, the formation mechanism of longitudinal cracks caused by uneven growth of the initial shell is determined. Based on the mechanism of longitudinal crack formation, by adjusting the performance parameters of the mold flux, the contradiction between the heat transfer control and lubrication improvement of the mold flux is fully coordinated, further reducing the incidence of longitudinal cracks on the surface of the casting thin slab. The results show that, using the optimized mold flux, the basicity increases from 1.60 to 1.68, the F- mass fraction increases from 10.67% to 11.22%, the Na2O mass fraction increases from 4.35% to 5.28%, the Li2O mass fraction increases from 0.68% to 0.75%, and the carbon mass fraction reduces from 10.86% to 10.47%. The crystallization performance and rheological properties of the mold flux significantly improve, reducing the heat transfer performance while ensuring the lubrication ability of the molten slag. After optimizing the mold flux, a surface detection system was used to statistically analyze the longitudinal cracks on the surface of the casting thin slab. The proportion of longitudinal cracks (crack length/steel coil length, where each coil produced is about 32 m long) on the surface of the thin slab decreases from 0.056% to 0.031%, and the surface quality of the thin slab significantly improves.

Effect of cleaning parameters on the molten pool shape and molten slag dynamics in the corner scarfing process of the casting slab

In the steel industry, improving the hot charging and heat delivery ratio in the continuous casting of slabs and thick slabs can effectively reduce carbon emissions, lower energy consumption, and improve production efficiency. However, this puts very strict requirements on the surface quality of continuous-casting slab. Flame scarfing (or cleaning) technology is currently an important process in the metallurgy field, which can effectively remove impurities and crack defects on the surface and corners of continuous casting slab to ensure the quality and performance of the final product. Under the action of cleaning flame and iron oxide reaction heat, a cleaning molten pool is formed in the corner of the casting slab, and the shape and depth of the molten pool have an important influence on the cleaning effect. A three-dimensional mathematical model is developed to study the effect of slab cleaning speed and oxygen flow rate on the shape of the molten pool in the corners for the corner flame cleaning process. Simultaneously, a two-phase flow volume of fluid (VOF) model for gas-slag interactions is employed to examine the motion behavior of the molten slag. The results showed that when the operating conditions changed, the cleaning speed increased by 1 m/min, the length of the wide and narrow sides decreased by approximately 9.2 mm, and the depth of the corner pool decreased by approximately 5.3 mm. Moreover, a slag-blocking device was designed to mitigate the issue of slag splashing effectively based on the numerical simulation results compared with and without the slag-blocking device. These study works provide beneficial theoretical support and practical guidance for refining and optimizing flame-cleaning techniques.

Characteristic analysis of mold level fluctuation during continuous casting of Ti-bearing IF steel

Mold level fluctuation has always been one of the key factors in slab quality control. Abnormal fluctuations can easily cause slag entrainment and form surface defects of hot-rolled and cold-rolled steel sheets, thus reducing the product qualification rate. In this study, mold level fluctuation data was collected during Ti-bearing Interstitial Free (IF) steel in a stable state for a complete casting sequence in a certain factory. The mold level fluctuation is analyzed using the discrete wavelet transform (DWT) method, and its characteristic values are classified based on frequency. Combined with the corresponding process parameters, the causes were traced during abnormal fluctuation characteristic values. It was found that the formation of abnormal mold level fluctuation mainly comes from two aspects. On the one hand, there are random fluctuations in the low-frequency band, and on the other, there are clustered fluctuations in the relatively high-frequency band. There is always a rising trend in mold liquid levels when there are random abnormal fluctuations in the low-frequency band. There is a delay of approximately 0.1412 s in the feedback of the stopper rod to the mold level fluctuation. The major causes of the low-frequency random fluctuations include variations in the tundish weight, casting speed, and mold width, and the clogs peeling. The clogging of the side hole at the submerged entry nozzle (SEN) is the primary cause of abnormal clustered fluctuations in the high-frequency band. These are certain relationships with clogging, whether it is high-frequency clustered or low-frequency random abnormal fluctuations. Without a doubt, this is a crucial link that limits the slab quality.

Effect of Casting Temperature Control on Microstructure and Properties of Continuously Cast Zr-Based Bulk Metallic Glass Slabs

In this study, a novel crawler-type continuous casting (CC) technology was designed to efficiently and cost-effectively produce bulk metallic glass (BMG) slabs. As a crucial process parameter, casting temperature has a significant impact on the operation of CC devices and the quality of slabs. CC experiments of the Zr41.2Ti13.8Cu12.5Ni10.0Be22.5 (Vit1) BMG slab were carried out at the casting temperatures of 1073 K, 1123 K, and 1173 K, and the microstructure and properties of slab samples were analyzed and studied. The experimental results indicate that the BMG slabs can be prepared by CC at 1173 K and 1123 K. When the temperature is reduced to 1073 K, the Be12Ti crystal phase precipitates inside the CC slab, which has a certain impact on the thermal stability and compressive performance of the slab. The control of casting temperature does not affect the glass-forming ability (GFA) of the slab in the CC process.

Fluid Flow, Solidification and Solute Transport in Slab Continuous Casting with Different S-EMS Installation Positions

During continuous slab casting, strand electromagnetic stirring (S-EMS) has a significant effect on improving the slab quality. In the current work, a numerical model based on the practical slab continuous casting machine and coupled electromagnetic field, flow field, solidification, and solute transport was established to investigate and evaluate the effect of the S-EMS installation position with various current intensities on metallurgical behavior. The model was verified by magnetic field measurement, infrared camera, and nail shooting experiments. The results show that moving the S-EMS installation position to the solidification end reduces the stirring effect due to the skin effect and the increasing thickness of the slab shell. A higher installation position is beneficial for improving the equiaxed grain rate, while a lower one is beneficial for reducing carbon segregation. The maximum segregation index and range decrease from 1.26 to 1.2 and from 0.42 to 0.36 with the installation position being decreased from −3 m to −12.8 m, respectively. The industrial trials show that S-EMS installed at 3 m has a significant effect on expanding the equiaxed grain zone and a deteriorating effect on reducing carbon segregation.

Numerical Simulation of Segregation in Slabs under Different Secondary Cooling Electromagnetic Stirring Modes.

Secondary cooling electromagnetic stirring (S-EMS) significantly impacts the internal quality of continuous casting slabs. In order to investigate the effects of S-EMS modes on segregation in slabs, a three-dimensional numerical model of the full-scale flow field, solidification, and mass transfer was established. A comparative analysis was conducted between continuous electromagnetic stirring and alternate stirring modes regarding their impacts on steel flow, solidification, and carbon segregation. The results indicated that adopting the alternate stirring mode was more advantageous for achieving uniform flow fields and reducing the disparity in solidification endpoints, thus mitigating carbon segregation. Specifically, the central carbon segregation index under continuous stirring at 320 A was 1.236, with an average of 1.247, while under alternate stirring, the central carbon segregation index decreased to 1.222 with an average of 1.227.

Continuous casting tundish quality study by mathematical & physical simulations, economics with plant result justifications

A combination of physical modeling, computational fluid dynamics modeling, and economics with plant trial studies was performed for quality improvement of Special Bar Quality (SBQ) and Oil Country Tubular Goods (OCTG) grade tundish steels. The present study consists of operating parameters like inert gas shrouding, non-isothermal conditions, and flow control devices (FCD) used on the billet product and slab quality. This work uses mathematical modeling using the fluid volume and discrete phase method (DPM) and the standard k-ε turbulence model validated with one-third scale physical water model experiments. A strong correlation between the physical model and computational simulation was found with rejection ratio and inclusion counts. Data about customer demands correlated with operating parameters for proper plant insights with an economic study to predict the cost-related issue. With the incorporation of FCD, the weight of the tundish skull was reduced by 6–10 M USD/year with a simulation studies expenditure of around 200 K. FCD also reduced the customer complaint index (CCI).

Modeling effects of swirl burners on the heating quality of slabs and flame morphology in a walking-beam reheating furnace

This paper developed a model of zone segment swirl burners to realize individual separation of swirl burners within a CFD model of an industrial-scale walking-beam reheating furnace. Numerical results are validated against the experimental measurements, demonstrating good agreement and credibility. Leveraging this model, a comprehensive investigation on the effect of swirl angle on the flame morphology and the slab heating quality has been conducted. Comparing various swirl angles (0°, 25°, 45°, and 65°) provides valuable insights into their impact on flame morphology, and slab heating quality. A swirl angle of 25° has been identified as optimal, yielding the maximum flame area within the furnace, measuring 326.09 m2. Furthermore, it reduces the maximum absolute temperature deviation of the discharged slab’s top surface centerline to 7.64 K, marking a substantial 25.83 % reduction compared to the 0° angle. These results highlight the critical role swirl burners play in the reheating furnace and identify the optimal swirl angle for effectively enhancing both the economic benefits and product quality in industrial processes.

An imbalanced small sample slab defect recognition method based on image generation

The surface quality of slabs has a profound impact on the subsequent performance and quality of steel. Accurate detection and classification of surface defects are crucial for improving steel quality. However, online visual inspection in the steel industry faces challenges such as sparse data, unclear features, sample imbalances, and impeding the application of deep learning in slab defect detection. To address these challenges, this paper introduces a novel approach utilizing the Slab Defect Generation (SDG) network to generate additional images by training on imbalanced small samples of slab defects, thereby constructing a comprehensive defect database. This methodology significantly enhances the efficiency and accuracy of deep learning in slab defect detection. Furthermore, an improved loss function is proposed specifically for the You Only Look Once version 5 (YOLOv5) model to augment the training of challenging samples. Experimental validation confirms the superiority of our method in terms of both image generation quality and defect-recognition compared to State-Of-The-Art (SOTA) models. The accuracy achieved by our approach is 98.6 %, outperforming the second-ranking model with an accuracy of 90.1 %.Index Terms—Data Enhancement, Deep Learning, Defect Recognition, Machine Vision, Neural Networks, Small sample learning.

Numerical Study on Characteristic Positions and Transition of Flow Patterns in a Slab Continuous Casting Mold

The flow pattern in an opaque mold cannot be readily visible, and worker experience plays a major role in controlling it, even though it has a significant impact on slab quality in a continuous casting (CC) mold. An Eulerian–Eulerian two‐fluid model is used to comprehensively study the two‐phase flow of argon and molten steel in a slab CC mold. The positions of vortex centers in upper/lower recirculation zones and the impingement point of jet flow on the narrow face of mold are identified and their distribution is analyzed. The interactive effects of casting speed, argon flow rate, and immersion depth of the submerged entry nozzle (SEN) on the flow pattern inside the mold are revealed. 2D and 3D flow pattern regimes are plotted and the boundary lines and boundary surfaces are fit with exponential functions and ternary functions, respectively. To obtain a double roll flow in the slab CC mold investigated, the relation among argon flow rate (), casting speed (), and the immersion depth of the SEN () should satisfy, .

Automatic Detection of Cast Billet Dendrite Based on Improved Hough Transform

Primary dendrite information is one of the most important metrics to measure the quality of continuous cast slabs. The contrast of low magnification images is very low under the influence of illumination and sampling devices, so the traditional dendrite detection method has the problem of missed detections. We propose an automatic dendrite detection method based on an improved Hough transform, which effectively improves the accuracy and efficiency of primary dendrite detection. By using the local grayscale features of the image, a genetic algorithm-based local contrast enhancement algorithm is proposed. Compared with the traditional contrast enhancement algorithm, it can retain all the information of the dendrites. Combined with the image binarization method based on Hessian matrix, we can obtain more detailed information about the dendrites. According to the continuity and solidification characteristics of dendrites, the Hough transform is improved to extract dendrite information, which effectively reduces the computational cost of the Hough transform. The experimental results show that the method of this paper has versatility, and the error is four pixels compared with the manual method, which can provide a reliable basis for the subsequent judgement of the quality of cast billets.

Stabilizing Flow of Molten Steel in Mold during Slab Continuous Casting through Electromagnetic Swirling Flow in Nozzle

Bias flow of molten metal in slab mold caused by unstable flow from submerged entry nozzle can deteriorate the slab quality during continuous casting. In this study, a novel electromagnetic swirling flow in nozzle (EMSFN) technique, which utilizes electromagnetic force to stabilize the flow in the nozzle and subsequently control the flow in the mold, is proposed. The mechanism for controlling unstable flow through EMSFN is explored through numerical simulation and water model experiments. In the results, it is shown that the molten steel is rotated under the effect of magnetic field and flows into the mold along the upper edge of the nozzle outlet, which weakens the impact of molten steel on the bottom of nozzle and stabilizes the outflow from nozzle. The flow field is consistently symmetrical on both sides of the nozzle. The impact depth of molten steel flowing down along the narrow sides of the mold on both sides is greatly reduced. The surface velocity on both sides of the nozzle changes uniformly. The range of surface velocity variation with EMSFN is only 10% of that with a conventional nozzle. The EMSFN technique can help prevent slag entrapment and improve the flotation of inclusions and bubbles.

Distribution of Large‐Size Inclusions in Transition Slabs for Automotive Exposed Panel Steel

In order to improve the quality of the transition slabs, the large‐size inclusions in 28 m‐long transition slabs are studied by large sample electrolysis and thermodynamic analysis. The results reveal that the length of transition slabs influenced by ladle exchange is 17 m, which is 4 m before the second steel ladle casting and 13 m after the casting. Large‐size inclusions in transition slabs can be divided into five kinds of Al2O3, Al2O3‐CaO, Al2O3‐CaO‐SiO2, Al2O3‐CaO‐MgO, and entrapment slag. The average contents of total inclusions, the inclusions in the range of 30–100 μm, those of 100–200 μm, and those larger than 200 μm in the transition slabs are 4.8, 19, 2.8, and 4.2 times higher than those in the normal slabs, respectively. For the large inclusions greater than 200 μm, the average contents of the Al2O3, Al2O3‐CaO‐SiO2 inclusions, and entrapment slags significantly increase in the transition slabs, being 9.4, 13.1, and 2.4 times higher than those in the normal slabs, respectively. The sources of Al2O3, Al2O3‐CaO‐SiO2 inclusions, and entrapment slags should be the secondary oxidation in tundish, entrapment of tundish flux, and entrapment of mold powders, respectively.

Reducing skid marks on steel slabs by developing an improved design scheme of water beam

Due to the existence of cooling water pipes and thermoduric skids in the walking beam type reheating furnace, skid marks always occur on the bottom of the steel slab and the quality of the steel slab is seriously affected. In this paper, the coupled heat transfer model among steel slab, water beam, furnace gas and furnace walls is established to accurately simulate the reheating process of the steel slab. The discrete ordinates method (DOM) is adopted to solve radiative heat transfer problem in reheating furnace. To get closer to the real situation, the relative movement between steel slab and thermoduric skid is taken into account strictly. The formation process of skid mark is clarified based on the calculated results of coupled heat transfer, and an improved design scheme for water beam is proposed to make the new skid marks produced after water beam dislocation not overlap each other, which effectively reduces the skid marks. Our study can provide helpful advising for the improvement of steel slab quality and the design of water beam structure in reheating furnace.

Effect of High Mass Ratio of CaO to Al2O3 on Properties of Slag Containing 10% SiO2

In this study, the viscometer is used to evaluate the viscosity of slag containing 10% SiO2 with varying CaO/Al2O3 ratios. When CaO/Al2O3 ratio increases in the 3.00–4.00 range, the viscosity exhibits a non‐monotonic behavior characterized by an initial decrease followed by an increase, with a minimum value of 0.046 Pa·s observed at 1673 K. The slag with a CaO/Al2O3 ratio above 3.00 has relatively low and stable viscosity within the range of 1373–1673 K, which is beneficial for slab quality of high‐aluminum steel. X‐ray diffraction and Raman spectroscopy are used to better understand the viscosity evolution of slag containing 10% SiO2. A higher CaO/Al2O3 ratio depolymerizes network structures due to the breaking effect of free oxygen O2−. Upon surpassing a CaO/Al2O3 ratio of 3.50, the transformation of the crystallization phase occurs from CaO·SiO2 to 2CaO·SiO2. Additionally, a higher CaO/Al2O3 ratio promotes the precipitation of the 11CaO·7Al2O3·CaF2 crystal in the slag.