Modelling and control of coiling entry temperature using interval type-2 fuzzy logic systems

Abstract

The set-up of the cooling water applied to the strip as it traverses the runout table in order to achieve the coiler entry temperature was made by an intelligent model implemented using interval type-2 fuzzy logic systems. The model uses as inputs the targets for coiling entry temperature, strip thickness, finish mill exit temperature and finishing mill exit speed. The experiments of this application were carried out for three different types of coil in a real hot strip mill. The results proved the feasibility of the system developed for coiler entry temperature prediction. Comparison with the online type-1 fuzzy logic based model shows that the proposed interval type-2 fuzzy logic system improves performance in coiler entry temperature prediction under the tested condition.     

Application of Cooling Water in Controlled Runout Table Cooling on Hot Strip Mill

The controlled runout table cooling is essential in determining the final mechanical properties and flatness of steel strip. The heat of a hot steel strip is mainly extracted by cooling water during runout. In order to study the heat transfer by water jet impingement boiling during runout, a pilot facility was constructed at the University of British Columbia. On this pilotfacility, the water jet impingement tests were carried out under various cooling conditions to investigate the effect of processing parameters, such as cooling water temperature, water jet impingement velocity, initial strip temperature, water flow rate, water nozzle diameter and array of water nozzles, on the heat transfer of heated strip. The results obtained contribute to the optimization of cooling water during runout.     

Experimental study of boiling heat transfer during subcooled water jet impingement on flat steel surface

Abstract

The growth in demand for high quality metal alloys has placed considerable emphasis on the type of cooling methods used in manufacturing processes, in particular, the production of highly tailored steel through controlled cooling on the runout table. The present study focuses on the heat transfer (cooling of hot rolled steel strips) on a runout table. The purpose of the study was to develop an efficient experimental method and collect temperature data under conditions similar to those that occur during industrial runout table conditions in a steelmill. Surface and internal temperatures were measured during transient cooling of a flat, upward facing fixed steel plate cooled by a highly subcooled single, circular, free surface jet of water. Measurements were made at stagnation and several streamwise distances from the stagnation point. A numerical, finite difference model was applied to calculate the surface heat flux using measured temperatures. The effect of water flowrate and subcooling on the overall heat transfer with emphasis on the maximum heat flux is discussed.     

Modelling of microstructural evolution during accelerated cooling of hot strip on the runout table

Microstructural evolution in the hot strip after finishing and subsequent accelerated cooling on the runout table has been modelled in order to assess their suitability for further processing. Transient heat transfer and kinetics of phase change comprising austenite to ferrite plus pearlite have been coupled to ascertain temperature profile, taking into accout the heat generated during phase change. Johnson-Mehl-Avrami relation together with Scheil's rule of additivity have been invoked. Several process parameters such as, coefficient of heat transfer, temperature at the exit of finishing stand, thickness and the speed of strip have been varied to determine their influence on the extent of phases engendered on the runout table. It has been demonstrated that greater spreadout in cooling arrangement with relatively lower heat transfer coefficient ensures homogeneity in microstructure. Cooling from comparatively higher finishing temperatures may result in greater microstructural uniformity. Two grades of steel – namely 0.05C-0.23Mn-0.015Si and 0.08C-0.37Mn-0.06Si – were chosen to carry out plant trials to validate the model. Special features of the microstructure have been brought out and the mechanical properties have been correlated.     

珠江钢厂CSP热连轧层流冷却热过程模拟研究

分析了带钢层流冷却的传热过程，将相变潜热引入到层流冷却热过程数学模型，用过程模拟的方法研究了珠江钢厂CSP热连轧层流冷却系统。讨论了喷水方式、喷嘴位置、板速和板厚对带钢温度场分布的影响。结果表明建立的模型对于珠钢CSP热连轧层流冷却系统有较好的适应性，能够对实际生产起到较好的指导性作用。     

Modelling recalescence after stock reduction during hot strip rolling

Abstract

The relationships between stock recalescence time/distance and process variables, such as exit thickness, reduction, rolling speed, work roll diameter and slab–roll heat transfer coefficient during hot strip rolling, have been established. The behaviour of the temperature gradient was analysed and used to estimate the slab and transfer bar mean temperatures from measured surface temperature in three hot strip mills located in northeast México. It was found that the recalescence critical variables, in order of importance in minimising temperature measurement variation, are slab–roll heat transfer coefficient, reduction, exit thickness and roll speed.     

Self-Learning and Its Application to Laminar Cooling Model of Hot Rolled Strip

The mathematical model for online controlling hot rolled steel cooling on run-out table （ROT for abbreviation） was analyzed, and water cooling is found to be the main cooling mode for hot rolled steel. The calculation of the drop in strip temperature by both water cooling and air cooling is summed up to obtain the change of heat transfer coefficient. It is found that the learning coefficient of heat transfer coefficient is the kernel coefficient of coiler temperature control （CTC） model tuning. To decrease the deviation between the calculated steel temperature and the measured one at coiler entrance, a laminar cooling control self-learning strategy is used. Using the data acquired in the field, the results of the self-learning model used in the field were analyzed. The analyzed results show that the self-learning function is effective.     

The thermal and metallurgical state of steel strip during hot rolling: Part I. Characterization of heat transfer

A technique using intrinsic thermocouples was developed to monitor the thermal response of steel samples during hot rolling. A series of hot-rolling tests was conducted with the thermocoupleinstrumented samples on CANME’s pilot mill to simulate individual stands of Stelco’s Lake Erie Works hot-strip mill. A mathematical model of heat transfer in the roll bite has been employed to back calculate the roll/strip interface heat-transfer coefficients for lubricated and unlubricated conditions. The influence of reduction, rolling speed, and prerolling on roll-strip heat transfer has also been examined. For unlubricated rolling tests, the heat-transfer coefficient in the roll bite increased with time, reaching a steady-state value of 57 kW/m² °C. The corresponding number for the lubricated tests was 31 kW/m² °C. The observed variation in the interface heat-transfer coefficient with increasing strain and interface pressure points to a strong dependence on the real area of contact between the strip and rolls. Therefore, it appears that heat transfer between the two surfaces occurs primarily by conduction across asperity contacts. The high heat-transfer coefficients attained at the roll/strip interface promote chilling of the strip to a depth of approximately one-eighth of the thickness. To validate the overall heattransfer model, predicted surface temperatures of the strip have been compared with interstand temperature measurements obtained on the industrial mill using pyrometers. Formerly Graduate Student, The Centre for Metallurgical Process Engineering, The University of British Columbia     

Prediction of shape defects during cooling of hot rolled low carbon steel strip

Abstract

Shape defects are found in hot rolled steel strip when unwrapping tightly wound coils. This problem is particularly acute in thin strips that were considered to be defect free while processing. A model developed to predict the occurrence and magnitude of such defects in hot rolled low carbon steel strip is described in the present paper. The model assumes that the strip is free of shape defects as it exits the last stand of a continuous mill, but, as a result of processing conditions, thermal and microstructural gradients are present across the width of the strip. It is considered that the variation of ferrite and austenite mixture is caused by the chemical composition of the steel and the actual temperature of the strip. On cooling to room temperature, the distribution of both temperature and microstructure will cause variation in the local contraction that the steel is subjected to, and will promote shape defects.     

New parameters for the description of hot rolled strip transverse temperature distribution: preliminary applications

Abstract

Nowadays, it is possible to find experimental data about the longitudinal temperature distribution for a hot rolling strip production. However, it is much more difficult to obtain experimental results on the transverse temperature distribution on the strip surface. After a systematic analysis of the methods and results in the literature, the experimental data collected using a specific experimental apparatus to measure the transverse strip temperature distribution out of the last finishing stand of a 1800 mm wide thin hot strip rolling mill are presented. In order to logically classify all the results by identifying the main factors that influence the strip temperature profile, it is proposed to describe more clearly four new parameters of the strip thermal profiles which would allow the investigation of the reason for uneven transverse temperature distributions. The relationship between strip temperature distribution, strip geometry and temperature itself is also studied to provide a basis to build a mathematical model for the current problem.     

人工神经网络在层流冷却卷取温度预报中的应用

针对宝山钢铁（集团）公司2050热连轧层流冷却系统，采用神经网络与数学模型相结合的方法，给出优化的层流冷却对流换热系数，以实现准确地预报卷取温度的目的。结果表明，采用神经网络计算出的对流换热系数后，卷取温度的计算值与实测值的标准差降低了22．84％，效果显著。     

Improvement of Prediction Method for Strip Coiling Temperature

Thecoilingtemperatureisoneoftheimportanttechnologicalparametersaffectingthefinalmechani calpropertiesofstrip[1,2 ] .The purposeofcoilingtemperaturecontrolistomakestripcooltorequiredcoilingtemperaturefromhighertemperatureforap propriatemicrostructureandmechanicalproperty .Atpresent ,thecontrolmodelofcoilingtemperatureforBaosteel 2 0 5 0millisaself adaptingempiricalmodel.Thoughthecontrolissatisfactory ,theout of toleranceofcoilingtemperatureisstillobservedinproduction .Itwasconcludedbytheinvest…     

Thermal behaviour of a moving steel strip cooled by an array of planar water jets

A mathematical model has been developed to predict the temperature distribution in a moving strip of steel cooled by an array of planar water jets. Experimentally determined nucleate boiling and analytically obtained single-phase convection and film boiling heat transfer coefficients are used as convective boundary conditions, and thermophysical property variations of the steel with temperature are considered in the analysis. The model equation for the strip temperature distribution is solved numerically, and the model is validated by comparing predicted coiling temperatures with measurements obtained on the runout table of a steel mill.     

Development and deployment of online multifrequency electromagnetic system to monitor steel hot transformation on runout table of hot strip mill

Abstract

This paper presents a simulation and experiment study on an electromagnetic (EM) sensor system for monitoring the phase transformation of steel strip on the runout table (ROT) of the hot strip mill in Tata Steel IJmuiden. The sensor head contains an H shaped magnetic core and is excited simultaneously at multiple frequencies. A simulation study linking the output of the EM system, in the form of a mutual induction spectrum, to the transformation processes within the steel strip is presented. This is performed by linking the results of thermodynamic models of the transformation behaviour of the steel strip (modelled with the TITAN mill model, property of Tata Steel) with the EM response of the sensor system (modelled with Ansys Maxwell 3D). The simulations are able to show the induction spectra that would be measured for a particular mill set-up and steel strip at different positions over the length of the ROT. The paper further describes the construction and deployment of the sensor head on the IJmuiden hot strip mill and presents the first results from this type of system with data taken during normal production on the mill.     

带钢超快速冷却条件下的换热过程

 分析了轧后加速冷却过程中带钢表面的局部换热机理，认为冷却系统实现超快速冷却的关键在于扩大带钢表面射流冲击换热区的面积。确定了薄带钢实现超快速冷却所需的对流换热系数，并采用有限元分析工具ANSYS模拟得到了超快速冷却条件下不同厚度带钢的温度场。温度场的分布表明薄带钢在超快速冷却过程中具有较好的温度一致性。同时还表明随着带钢厚度增加，超快速冷却条件下厚度方向的温度梯度显著增大，对于带钢内部组织的均匀性将产生不利的影响。带钢厚度范围应是超快速冷却技术实际应用过程中的重要考虑因素。     

热轧带钢控制冷却技术的发展

新钢种开发和用户对板带产品质量越来越严格的要求使得轧后控制冷却得到高度重视,不但要求实现目标卷取温度控制,冷却速度控制还要求实现冷却路径控制和微观组织结构和性能控制.从冷却换热形式、数学模型、控制策略、质量控制思想四个方面阐述了控制冷却技术的发展.     

Modelling of heat transfer in hot strip mill runout table cooling

The need for accurate prediction and control of cooling profiles of steel strips on runout tables has led to the development of a mathematical model that is able to predict coiler temperatures under any given condition with an accuracy of ± 14 °C as well as calculating the entire temperature profile of a steel strip with sufficient accuracy. Comparisons with online strip temperature data at various locations of the runout table, which were obtained by a new experimental procedure, show that the effect of single cooling headers on the thermal response of a steel strip can be predicted. The model takes into account all relevant thermodynamic effects by means of a statistical approach. Heat transfer to the environment, steel thermophysical properties and phase transformation are modelled using B‐splines. Model adaptation is realised by fitting calculated and measured coiler temperatures of approximately 40000 strips with a least square method in order to gain optimal base values for the B‐spline functions. During model development special attention was paid to the model's capability of being re‐adjustable to a large variety of conditions as well as its local behaviour. Therefore, concepts like temperature‐dependent heat transfer coefficients, which are applicable only to one specific plant, have been avoided in favour of a more generalised formulation of the model that helps to gain insight into the physics of the processes involved, i.e. heat transfer of subcooled jet impingement boiling and film boiling. It was found that both cooling water and steel surface temperature have a large influence on heat transfer whereas the influence of strip speed can be neglected.     

Modelling the Temperature Distribution along the Length of Strip during Hot Rolling Process

Hot strip rolling process includes four main stages, which are reheating process, roughing and finishing process, laminar‐cooling process, and coiling process respectively. Temperature is the most sensitive parameter and has direct effect on the microstructural evolution and further the mechanical properties, and the accurate control of temperature guarantees the quality of products and homogeneity of properties along the strip length. However, for the conventional hot strip rolling process, thermal history along the strip length is very complex, the related temperature variation concerns air cooling, water cooling, heat transmission by roll contact, heat generation by deformation and friction. Based on the actual hot strip mill, the thermal models are established in this paper to simulate the temperature distribution along the whole strip length from the reheating furnace exit to the down coiler. Different interface heat transmission coefficients are selected for the scale breaking and spray water‐cooling process, and a self‐learning algorithm is thus employed to improve the calculation accuracy. This model is characterized as simple and fast, and convenient for on‐line/off‐line prediction of temperature. Finally the simulated results are verified by the on‐line temperature detection at typical points such as roughing exit (RT2), finishing exit (FT7) and coiling position (CT).     

Analysis of flow field and temperature distribution in compact strip production casting process

Abstract

A three-dimensional finite difference model has been formulated, using the commercial code CFX4, to describe the fluid flow and heat transfer in the funnel mould and secondary cooling segment of the compact strip production (CSP) casting process. Through simulation and computation with the established simulation model, influences of the factors such as casting speed, casting superheat, immersion depth of submerged entrance nozzle, amount of cooling water in the secondary cooling segment on flow field and temperature field in the funnel mould and secondary cooling segment of CSP technology were analysed.     

Ultra Fast Cooling of a Hot Steel Plate by Using High Mass Flux Air Atomized Spray

In the current research, the ultra fast cooling (UFC) of a hot stationary AISI‐304 steel plate has been investigated by using air atomized spray at different air and water flow rates. The initial temperature of the plate, before the cooling starts, is kept at 900°C or above. The spray was produced from a full cone internal mixing air atomized spray nozzle at a fixed nozzle to plate distance; and the average spray mass flux was varied from 130 to 370 kg m^?2 s by selecting different combinations of air and water flow rates. The surface heat flux and surface temperature calculations have been performed by using INTEMP software and the calculated results have been validated by comparing with the measured thermocouple data. The heat transfer analysis indicates that the cooling occurs in the transition boiling regime up to surface temperature of 500°C and thereafter it changes to nucleate boiling regime. The superposed flow of air on the hot plate enhances the cooling in the temperature range of 900–500°C by sweeping the partially evaporated droplets from the hot surface. However, due to the high percentage of fine water droplets in the resultant spray produced at higher air flow rates, the maximum cooling rate is achieved at the medium air flow rate of 30 N m³ h^?1. The cooling rate (182°C s^?1) produced by an air atomized spray is found to be in the UFC regime of a 6 mm thick steel plate. The findings of this research can be considered as the basis for the fabrication of cooling system in the run‐out table of a hot strip mill.