Hot Strip Rolling Mill Research Articles

Neural network modelling of the Nb effect on mechanical properties of the ferritic bainitic dual-phase steel

ABSTRACT The production of low-alloy advanced high-strength steels such as the dual-phase (DP) steel with ferritic-bainitic microstructure using a hot strip mill is challenging in terms of consistent mechanical properties-based DP steel without violating the hot strip mill rolling capacity. In the present study, the Artificial Neural Network (ANN) technique was employed to develop tensile strength, yield strength and %Elongation models which can cater to complex relationships between the DP steel mechanical properties as a function of steel composition and rolling parameters. Furthermore, ANN models were used to predict the Nb effect on the mechanical properties of the DP steel. Model prediction and validation confirmed that niobium has a notable influence on mechanical properties. Finally. Nb’s role during hot rolling was reviewed and justified.

Simulation of mechanical wear of work rolls of a wide-strip hot rolling mill using machine learning methods

Modern methods of modeling a mechanical wear of hot rolling mill work rolls under industrial conditions are presented. The use of machine learning algorithms based on multidimensional linear regression, decision trees, and neural networks made it possible to describe more accurately the features of work roll wear depending on many technological factors. At the same time, the data set from the production database was subjected to additional classification for each technological parameter in a certain range. This classification approach significantly improved the quality of the output model for all major metrics. The input variables for training were the main technological factors measured in the finishing group of stands during the campaign of each work roll. The output parameters – wear curves on a roll grinder measured after roll changes. 93 input parameters were used to calculate each of the 300 output values of mechanical wear along the length of the roll barrel and to train machine learning algorithms. Roll wear forecasting models based on multivariate linear regression, random forest, gradient boosting and neural networks have been developed. A comparative analysis of the developed models with classical approaches for calculating the work roll mechanical wear showed that machine learning methods have a higher accuracy. An approach and recommendations for the introduction of new models to the automated process control system of hot strip rolling mills were proposed.The research was carried out within the framework of the program of strategic academic leadership of the Russian Federation "Priority 2030", aimed at supporting the development programs of educational institutions of higher education, the scientific project PRIOR/SN/NU/22/SP5/26 "Creation of innovative digital tools for the use of applied artificial intelligence and advanced statistical analysis of big data in technological processes of manufacture of metallurgical products", as well as within the framework of scientific and technical cooperation between JSC Vyksa Metallurgical Plant and Bauman MSTU.

Study on Work Roll Vertical Vibration Under Periodic Spalling of the Oxide Film

The dynamic effect of work-roll oxide-film periodic spalling on vertical vibration in a hot strip rolling mill was studied. Based on dynamic monitoring test analysis, the friction of the work-roll surface under oxide-film periodic spalling is discussed. Using an average rolling pressure formula, the rolling force under the dynamic vertical vibration and the time-varying friction coefficient were found. A two-degrees-of-freedom dynamic system of the hot strip mill was established, considering the roller system symmetry. Based on the multiscale small-parameter perturbation method, the main resonance characteristic of work-roll vertical vibration has been explored. Using the 1780-mm hot strip mill in Chengde Iron and Steel Co., Ltd., the dynamic characteristics of the system are analyzed when oxide-film periodic spalling occurs on the work roll. The results are consistent with the test data, which show the effect of oxide-film spalling on vertical vibration. The simulation results for resonance characteristics show that the vibration of the system can be effectively reduced by increasing the damping and adjusting the stiffness of the system. In rolling production, it is very important to ensure the stability of the oxide film in order to reduce fluctuation. This study provides a reference for the operation and maintenance of a rolling mill in the strip production process.

Multistep networks for roll force prediction in hot strip rolling mill

Hot rolling processes consist of multiple single rolling stand operating at high temperature and speed to achieve desired steel shapes and superior properties, via exerting roll forces that need to be accurately predicted by a model. The currently used model of the mill of this study shows prediction instability and is unable to accurately accommodate changes in steel grade. In this paper, we propose a machine learning based framework to establish a model that accurately predicts roll forces at each mill stands of the hot strip rolling mill. In contrast to the traditional models, the proposed expert system considers an individual model for each rolling stand and employs rolling history when predicting roll forces. The proposed model includes both steel chemistry and physical process parameters for its predictions. Our experimental results demonstrate that the proposed framework improves both prediction accuracy and stability by 40%–50% over the currently used mill model. The enhanced prediction accuracy will greatly improve dimensional and microstructural control, as well as ensuring the avoidance of mill overloads.

Optimization of continuous variable crown work roll shifting strategy using k‐nearest neighbors algorithm for hot strip rolling mill

AbstractAppropriate work roll shifting strategy in the finishing hot strip mill can make roll wear uniform and contour smooth. To eliminate the problem of roll shifting position duplication due to available roll shifting strategy, the optimized work roll shifting strategy is proposed in the hot strip rolling mill with continuous variable crown work rolls, using the k‐nearest neighbors algorithm. The self‐perpetuating parameter is used to describe the concentrated wear of the work roll. The position repeated parameter is put forward to evaluate the roll shifting position history. The relationship between concentrated shifting positions and uneven roll wear is analyzed based on in‐site data collected in a hot strip rolling mill. The program of optimization strategy is coded using language C. Off‐line simulation is made to obtain optimized shifting positions using the program. The comparison between in‐site engineering data and optimized shifting positions has been assessed using the scatter diagram and kernel density estimation. Comparison results show that the new strategy can solve the problem of shifting position duplication well. A simplified method is established to make it easy to apply the strategy to online applications, and the in‐site application shows that the optimization strategy has an excellent practical effect.

A novel mass flow controller for tandem hot rolling mills

In tandem hot strip rolling mills, the roll speed of the mill stands is synchronized to ensure a uniform mass flow. A uniform mass flow is desirable to keep the strip tension constant and thus avoid large movements of the loopers which are located between the mill stands in order to control the strip tension. This also improves the general thickness quality and prevents the strip from necking in case of too excessive strip tension. In typical state-of-the-art implementations, the roll speed is synchronized in a cascade master–slave control structure where the very last downstream mill stand serves as speed master and the upstream mill stands operate in a slave mode to make sure that the mass flow is kept constant. While the relation between the roll speeds in the classical synchronization control concept is typically constant, a thorough analysis of the mass flow reveals that the slip between the work rolls and the strip is time varying. Therefore, in order to ensure a uniform mass flow, a novel adaptive speed synchronization controller is proposed, which can be easily added to the existing control structure and is computationally undemanding. To this end, a mathematical model of the whole tandem mill including the complete control structure is derived and validated by measurements. Simulation results for this validated model prove that the proposed mass flow controller clearly outperforms the existing solution.

Possibilities for Renovation of Functional Surfaces of Backup Rolls Used during Steel Making

The paper presents the results of the research aimed at possibilities of renovation of functional surfaces of back-up rolls that are part of the hot strip rolling mill operating line using new types of additive materials. Experimentally, four melts of alloyed steel were produced in laboratory conditions from which four types of filler materials in the form of wires were made. They were made by pulling through dies to a diameter of 2.4 mm. The renovation of functional surfaces was performed on the batch of rolls with the outer diameter of 1000 mm and length 3000 mm. Cladding technology submerged arc welding (SAW) was applied for cladding of four spirals with 40 mm oscillation onto the base material of the 31CrMoV9 (EN 10085) sub-roll. The base flux marked WLDC 17-AWS A5.17-89 EM13K with basicity index 3 was used for cladding. The four-layer weld deposition was made to eliminate the effect of mixing the surfacing layers with the base material. The refurbished rolls were annealed after welding. Surface quality was assessed by visual inspection (VT) according to EN ISO 17637. The presence of internal errors was determined by ultrasound control (UT) in accordance with EN ISO 11666 and EN ISO 17640. The quality of the clad layers was analysed on metallographic sections using light microscopy. The microhardness of the individual clad layers was evaluated according to Vickers according to EN ISO 9015-2. Based on realized experiments it can be stated that the selected cladding parameter was suitable, and the overlay layers showed no surface or internal defects. Mechanical and tribological tests were carried out, but they showed significant influence of chemical composition of additive materials on mechanical properties, or wear resistance of the layers.

Optimal feedforward control of hydraulic drive systems with long pipelines

AbstractHydraulic drives are used in many technical systems, ranging from automotive and aerospace applications to industrial production systems. They provide high forces and torques at a compact design. The typical setup of hydraulic drive systems comprises a valve which controls a hydraulic cylinder or motor. In many practical applications, the valve is connected to the hydraulic cylinder via hydraulic pipelines, whose length can amount to several meters. Typically, the distributed‐parameter characteristics of these pipelines is not considered in the controller design. For very fast operation scenarios, wave effects can be excited which may cause a significant reduction of the control accuracy or even lead to instability of the closed‐loop system. In this paper, a model‐based control strategy is proposed which allows to systematically account for long pipelines. One main element is the spatial discretization of the partial differential equations of the pipelines by means of the spectral elemental method (SEM), which yields a low‐dimensional, but yet accurate model. Based on this model, an optimal feedforward control strategy is developed, which also enables to take into account actuator constraints. The resulting optimal control problem is efficiently solved on a moving horizon, resulting in a real‐time capable moving horizon trajectory planning strategy. An observer is added to account for uncertain model parameters. The high potential of the proposed approach is demonstrated in simulation by applying the method to the actuation system of a looper in a hot strip rolling mill.

Symmetry variable taper work roll technology for silicon steel profile control in hot strip mills

ABSTRACT Strip profile control in the hot rolling process plays an important role in guaranteeing high-precision profiles for silicon steel production in cold strip mills. A symmetry variable taper (SVT) work roll for the downstream finishing stands of hot strip mills is designed, which can be used for long stroke reciprocating shifting of work rolls, resulting in decreased edge drop and more uniform work roll wear contour. A finite element simulation model of 4-high mill based on ABAQUS was established, which improved the control characteristics of each process parameter for the strip profile when using the SVT work roll. The actual production data of the 1580 hot strip rolling mill equipped with SVT work rolls showed that the crown C25 of non-oriented silicon steel was reduced by about 5%, the edge drop was reduced by more than 15%, and the crown qualified rate was increased by 10%.

Dynamic Model of the Hot Strip Rolling Mill Vibration Resulting from Entry Thickness Deviation and Its Dynamic Characteristics

The vibration demolding of the crystallizer leads to slab thickness deviation in continuous casting processes. Therefore, in this paper, the dynamic model of the hot strip rolling mill vibration resulting from entry thickness deviation is proposed and its dynamic characteristics are studied. First, the dynamic model of vertical vibration in the hot strip rolling mill is established based on Sims’ rolling force model. Then, the model validity is certified by comparing the simulation with field test data from a 1580 hot strip rolling mill. Finally, we investigate the influence of model parameters on the dynamic characteristics of hot strip rolling mill vibration resulting from entry thickness deviation. The result indicates that hot strip rolling mill vibration resulting from entry thickness deviation can be reduced by increasing the area of the hydraulic cylinder piston side and the entry thickness as well as by decreasing the deformation resistance, rolling speed, and equivalent stiffness.

Load Distribution Optimization Based on Max-Min Ant Colony Algorithm in Hot Strip Rolling Process

A reasonable allocation of load distribution is expected when the full capacity of rolling equipment is exerted, and energy conservation and strip quality requirements are satisfied. In this work, the minimum value of the mill consumptive power summation and the optimum of the mill shape are used as the target function. Based on equipment parameters of a national hot strip rolling mill, a load distribution optimization method (subjected to certain constraints) was applied and a Max-Min ant-colony algorithm was subsequently used to optimize the load distribution of the mill. The optimization value was determined from the optimal path chosen by ants, and the optimum load distribution was obtained after a series of iterations. The compression ratio from upstream stands to downstream stands decreased gradually after optimization by this method, and the proportional crowns varied less than those associated with the traditional energy method. In fact, the amplitude of fluctuation was reduced by nearly 50%, which is favorable for strip shape controlling, and the total dissipative power was lower than that of the energy consumption method. Moreover, the overall power can be reduced by 4.19%, and an optimal rolling load distribution of the hot strip rolling process can be obtained.

Mill Scales Blended Polymer Composites For Electrical Insulation Application

Standalone composite films were prepared using modified polyester as a binder and waste iron oxides (mill scales) collected from a steel plant as inorganic filler. The morphology, structure, composition, strength and electrical insulation properties of polymer-iron composites were studied using various analytical techniques such as X-ray diffraction (XRD), Scanning electron microscope (SEM), Atomic force microscopy (AFM), optical microscopy, Fourier transform infrared (FTIR) spectroscopy, X-ray fluorescence (XRF), Brunauer–Emmett–Teller (BET) test, particle size analysis and electrical insulation test. The mill scales collected from the hot strip rolling mill (HSM) have found to comprise three different phases such as wustite, magnetite and hematite. Composites prepared using mill scales were showing three times higher strength compared to the mother polymer film. Electrical insulation of these composites were found to increase in the range of 55-230 MV/mm with increasing iron oxide content from 0.0125 g to 0.25 g in 2.5 g polymer. These results show a potential research field on the mill scales based composites for various advanced applications in improving insulation behaviour of materials which can withstand at higher temperatures and electrical stresses.

Asymmetric hydrodynamic roll gap model and its experimental validation

In tandem hot strip rolling mills, different friction between the rolls and the strip material on the upper and lower strip surface can occur due to asymmetric surface temperatures or different conditions of oil lubrication. To capture these effects, this paper presents a hydrodynamic roll gap model with asymmetric friction. Based on similarities between the rolled material and viscous fluids, fluid mechanics theory is used to derive this model. Due to the nature of this model, the influence of the rolling speed is inherently taken into account, which allows an accurate prediction of the rolling force and the forward slip. As an analytic solution for the hydrodynamic roll gap model is available, it is well suited for online applications in rolling plants. For validation of the proposed model, an experiment with asymmetric work roll roughness was performed. A specimen of steel strip with copper pins inserted was repeatedly rolled to visualize the material flow inside the roll gap for multiple passes. The resulting deformed copper pins were cut out of the strip and show good agreement with the deformation profiles calculated by the developed model.

Implementing multivariate statistics-based process monitoring: A comparison of basic data modeling approaches

Abstract The development of large interconnected plants has brought the need for the development of active and accurate performance monitoring methods. The commonly used approach to this problem is implementing the multivariate statistics-based process monitoring (MSPM). In MSPM, data modeling methods play the central role in developing normal operation models, based on which the monitoring statistics can be used to track the process operating performance. This paper seeks to perform a comparison study on the commonly used data modeling methods in the MSPM field, including principal component analysis, partial least squares, and canonical correlation analysis, to provide users and practitioners with informative details such that useful guidance can be offered to select the preferable methods. The interconnections between each two of them are first investigated. Then, dynamic extensions based on their static formulations including how they modify and resolve objective functions are revealed. Using the simulated data from the continuous stirred tank reactor benchmark process and real industrial data from the hot strip rolling mill process, parts of theoretical results are validated.

Optimal Parameter Identification for a Hydrodynamic Roll Gap Model in Hot Strip Rolling

When using modern model-based control concepts in a hot strip rolling mill, an accurate prediction of the roll force is crucial for the achieved control accuracy in terms of the strip thickness. Hence, the influence of various process parameters, e.g., lubrication, on the roll force is of central interest. Commonly used roll gap models are based on the slab method and are often not capable of describing these influences. The hydrodynamic roll gap model, however, can capture the influence of varying friction conditions between the strip and the work rolls. Varying friction conditions can be caused, for instance, by lubrication. This paper presents a combination of the hydrodynamic roll gap model with tailored material models for a more accurate prediction of the roll force in a tandem rolling mill. To parametrize the model, an optimization-based identification algorithm is proposed for unknown friction coefficients and material parameters. The identification algorithm is used on measurement data from an industrial hot strip rolling mill. A comparison with a commonly used roll gap model shows that the parametrized hydrodynamic roll gap model predicts the roll force with significantly higher accuracy.

A KPI-based process monitoring and fault detection framework for large-scale processes

Large-scale processes, consisting of multiple interconnected subprocesses, are commonly encountered in industrial systems, whose performance needs to be determined. A common approach to this problem is to use a key performance indicator (KPI)-based approach. However, the different KPI-based approaches are not developed with a coherent and consistent framework. Thus, this paper proposes a framework for KPI-based process monitoring and fault detection (PM-FD) for large-scale industrial processes, which considers the static and dynamic relationships between process and KPI variables. For the static case, a least squares-based approach is developed that provides an explicit link with least-squares regression, which gives better performance than partial least squares. For the dynamic case, using the kernel representation of each subprocess, an instrument variable is used to reduce the dynamic case to the static case. This framework is applied to the TE benchmark process and the hot strip mill rolling process. The results show that the proposed method can detect faults better than previous methods.

열간 조압연공정에서 판 캠버 저감을 위한 사이드 가이드 동적설정에 관한 연구

Bar camber is a phenomenon in which a material with a deformation gradient across its width is bent in the right or left direction in the roll gap. This paper proposes a dynamic setup approach for a side guide for reducing bar camber. A bar tracking scheme using a rotary encoder was adopted to fix an operation point for the side guide. The guiding pressure was utilized for measuring the actual width of the bar with camber. Based on the accurate position and width of the bar, the side guide was dynamically set and operated at the actual roughing train in a hot strip rolling mill. The amount of camber was reduced notably when the dynamic setup scheme was installed in the side guide. 78% of the bars tested had a camber in the range of <TEX>${\pm}20mm$</TEX>, which was an improvement of 27% in terms of production yield.

Designing of Hot Strip Rolling Mill Control System

Aimed at the complex demand of hot strip rolling mill in practicing, the configuration of the coiler and the technological process is analyzed. The arithmetic of coiling tension and the control process is introduced. The frame of the tension adjusting system is given. The coiler control system hardware is designed. The system is designed scientifically with steady control and meets demand of the market.

A Quality-Based Nonlinear Fault Diagnosis Framework Focusing on Industrial Multimode Batch Processes

This paper proposes a framework for quality-based fault detection and diagnosis for nonlinear batch processes with multimode operating environment. The framework seeks to address 1) the mode partition problem using a kernel fuzzy C-clustering method, and the optimal cluster number will be guaranteed by a between-within proportion index; 2) the diagnosis problem using a contribution rate method based on an improved kernel partial least squares (PLS) model, by which better detection and diagnosis performances are provided; and 3) the classification of online measurements using a hybrid kernel PLS regression and the Bayes inference theory, where the new coming measurement can be correctly assigned to its constituent mode. The whole framework is developed for batch processes, and applied to the hot strip mill rolling process. It is shown using the real industrial data that for faults affecting the thickness and flatness of the strip steel in this process, the detection and diagnosis abilities of the present methods are better compared with the existing methods.

Early Fault Diagnosis of Bearings Using an Improved Spectral Kurtosis by Maximum Correlated Kurtosis Deconvolution.

The early fault characteristics of rolling element bearings carried by vibration signals are quite weak because the signals are generally masked by heavy background noise. To extract the weak fault characteristics of bearings from the signals, an improved spectral kurtosis (SK) method is proposed based on maximum correlated kurtosis deconvolution (MCKD). The proposed method combines the ability of MCKD in indicating the periodic fault transients and the ability of SK in locating these transients in the frequency domain. A simulation signal overwhelmed by heavy noise is used to demonstrate the effectiveness of the proposed method. The results show that MCKD is beneficial to clarify the periodic impulse components of the bearing signals, and the method is able to detect the resonant frequency band of the signal and extract its fault characteristic frequency. Through analyzing actual vibration signals collected from wind turbines and hot strip rolling mills, we confirm that by using the proposed method, it is possible to extract fault characteristics and diagnose early faults of rolling element bearings. Based on the comparisons with the SK method, it is verified that the proposed method is more suitable to diagnose early faults of rolling element bearings.