Tandem Cold Mill Research Articles

Research on the Pre-Control of Side Scrap Blockage Failure during Trimming with the Side Trimmer

In the coupled pickling line and tandem cold mill (PL-TCM), the hot-rolled strip needs to be trimmed on both sides of the strip before the tandem cold rolling process to ensure stable operation of the rolling process. The equipment for trimming the strip is the side trimmer, and during trimming a failure of the side scrap blockage is often caused by the variation in the width of the hot-rolled strip and the deviation during the actual operation. For this problem, this paper established a finite element model of strip trimming by side trimmer, analyzed the influence of side scrap width, structure parameters, and strip specifications on the equivalent plastic strain at the trimmed position of the strip, and obtained the influence law of each factor during the trimming process. On this basis, by collecting the historical data of side scrap blockage failure of the side trimmer, the threshold value of the side scrap width setting is obtained. Combining the width data of the hot-rolled strip and the actual operation status monitoring of the strip in the inlet section of the PL-TCM, the side scrap blockage risk identification function and the speed reduction strategy of the side trimmer are designed to form the side scrap blockage pre-control model together. After applying the side scrap blockage pre-control model to a PL-TCM, a 40.5% reduction in side scrap blockage failures was achieved compared with the same length of time before the application, which achieved satisfactory results.

Optimization of Multi‐Segment Work Roll Profile for 1340 mm HC Tandem Cold‐Rolling Mills Based on DBSCAN and NSGA‐II Algorithms

To address issues with saturated work roll bending force (WRB), maximum contact pressure between the work roll and intermediate roll (QWI), and challenging flatness lifting in a four‐stand, six‐high tandem cold mill with a 1340 mm width, the density‐based spatial clustering of applications with noise algorithm and the non‐dominated sorting genetic algorithm II are used for optimal design and online application research of a five‐segment work roll profile. When compared to a flat roll and a parabolic roll profile with a maximum crown of 15 μm, the optimized roll profile decreases the secondary crown of the roll gap (CW2) by 5.99 and 1.055 μm, respectively, and the fourth crown of the roll gap (CW4) by 0.21 and 0.39 μm, respectively. Additionally, QWI in the field of roll gap crown adjustment decreases by 1.04 and 0.445 kN mm−1. Industrial testing shows that the average integrated value of flatness in rolling the four extreme specifications of 1340 mm tandem cold‐rolling mills lowers by 2.65 IU following the application of the new roll profile, and the average reduction of WRB in the last stand is 2.215 MPa.

Understanding the regulation ability of roll bending on strip shape in a CVC-6 tandem cold mill using a 3D multiple stand FE model

Roll bending is a common technique to regulate the strip shape in tandem cold rolling (TCR), but its regulation ability at each stand is poorly understood at present. In this study, based on a 3D multiple stand elasto-plastic finite element (EPFE) model, the effects of work roll bending (WRB) and intermediate roll bending (IRB) on the strip crown, strip flatness and elastic deformation of work roll (WR) were quantitatively studied at each stand in the TCR. Results show that the regulation abilities of WRB and IRB on the strip crown both show a downward tendency from Stand 1 (S1) to Stand 5 (S5), which both depend on the strip plastic rigidity. Moreover, under various WRBs and IRBs, the strip shape is mainly determined by the elastic deflection of WR in the upstream stand, while it is determined combinedly by the elastic deflection and flattening deformation of WR in the downstream stand. Furthermore, the regulation ability of WRB on the strip crown and quadratic flatness is at least 2.5 times larger than that of IRB. The experimental results show that the developed multiple stand EPFE model can well predict the trend of the quadratic and quartic flatness between coils. These findings help understand the influence mechanism of the roll bending on the strip shape and improve the strip shape by optimising the roll bending in the TCR.

Data-Driven Intelligent Recognition of Flatness Control Efficiency for Cold Rolling Mills

In the production process of strip tandem cold rolling mills, the flatness control system is important for improving the flatness quality. The control efficiency of actuators is a pivotal factor affecting the flatness control accuracy. At present, the data-driven methods to intelligently identify the flatness control efficiency have become a research hotspot. In this paper, a wavelet transform longitudinal denoising method, combined with a genetic algorithm (GA-WT), is proposed to handle the big noise of the measured data from each signal channel of the flatness meter, and Legendre orthogonal polynomial fitting is employed to extract the effective flatness features. Based on the preprocessed actual production data, the adaptive moment estimation (Adam) optimization algorithm is applied, to intelligently identify the flatness control efficiency. This paper takes the actual production data of a 1420 mm tandem cold mill as an example, to verify the performance of the new method. Compared with the control efficiency determined by the empirical method, the flatness residual MSE 0.035 is 5.4% lower. The test results indicate that the GA-WT-Legendre-Adam method can effectively reduce the noise, extract the flatness features, and achieve the intelligent determination of the flatness control efficiency.

Influence of intermediate roll shifting on strip shape in a CVC-6 tandem cold mill based on a 3D multi-stand FE model

Intermediate roll shifting (IRS) is widely used for improving the strip shape in the six-high tandem cold mill, but most related studies are limited to a single stand. To fill the knowledge gap, a three-dimensional (3D) multi-stand elastic–plastic finite element (FE) model was developed for a continuously variable crown (CVC)-6 tandem cold mill using data transfer, which was then validated by industrial experimental results. Based on this FE model, the effects of the IRS on the strip crown, strip flatness, loaded roll gap profile and contact normal stress between rolls at each stand were quantitatively analysed. The results show that from Stand 1 (S1) to Stand 5 (S5), the regulation ability of the IRS on the strip crown shows a decreasing trend, which depends on the strip plastic rigidity; in contrast, the regulation ability on the quadratic flatness experiences an obvious increase from S1 to Stand 4 (S4), then a drop at S5, while the IRS exerts little effect on the quartic flatness and quartic crown of the loaded roll gap. Moreover, the most uniform distribution of contact normal stress emerges at different IRSs from S1 to S5. These findings can contribute to a better understanding of the role of the IRS in controlling the strip shape during tandem cold rolling (TCR).

Development of Virtual Training Platform for Tandem Cold Rolling Mill Using Data Science and Digital Twin Technology

Abstract: An attempt has been made to develop Virtual Training Platform for Pickling Line Tandem Cold Mill (PLTCM) intended to deliver faster and enhanced learning experience of the process operator by leveraging Advanced Data Modelling, Data Science and Digital Twin Technology. Virtual Training Platform has modules for virtual tour of the plant, setup simulation, real-time rolling simulation, performance evaluation. Rolling Simulation has ANN based Automatic gauge control model and DNN based shape prediction model. Platform also comprises of a Natural Language Processing based chatbot for online query related to process line. Keywords: tandem cold Mill; Deep Neural Network (DNN); Virtual tour; Automatic Gauge Control (AGC), shape Control; chatbot

Noise Risk Assessment Using Noise Mapping Analysis Method and Noise Control at a Steel Company in Cilegon

Introduction: Physical factors found in the workplace can have an impact on occupational health and safety; one example of these physical factors is high noise intensity. One of the workplaces that have high noise intensity is a steel manufacturing company. The purpose of this study is to determine the noise risk based on noise mapping and analyse efforts that have been made in the Continous Tandem Cold Mill area in a steel company in Cilegon. Methods: The method used in this study was descriptive method. The variables used were the results of noise intensity measurements. The data were collected by means of literature study, field observation and noise measurements. The data obtained were then analysed using a descriptive method and were used as a basis in developing noise mapping. Results: Based on noise mapping, the welder area has the highest noise intensity of 91.1 - 94 dBA. Efforts to control noise intensity that have been carried out in the company are administrative control and personal protective equipment. Conclusion:From the results of noise intensity measurements in the Continous Tandem Cold Mill area of a steel company in Cilegon, it can be concluded that the measurement point is 76% - 100% and that the noise measurement points exceed the threshold value stipulated in the Regulation of the Minister of Manpower of the Republic Indonesia Number 5 of 2018. However, the steel company in Cilegon has made several efforts to reduce the noise intensity.Keywords: noise, noise mapping, steel company

Flatness Prediction of Cold Rolled Strip Based on Deep Neural Network with Improved Activation Function.

With the improvement of industrial requirements for the quality of cold rolled strips, flatness has become one of the most important indicators for measuring the quality of cold rolled strips. In this paper, the strip production data of a 1250 mm tandem cold mill in a steel plant is modeled by an improved deep neural network (the improved DNN) to improve the accuracy of strip shape prediction. Firstly, the type of activation function is analyzed, and the monotonicity of the activation function is deemed independent of the convexity of the loss function in the deep network. Regardless of whether the activation function is monotonic, the loss function is not strictly convex. Secondly, the non-convex optimization of the loss functionextended from the deep linear network to the deep nonlinear network, is discussed, and the critical point of the deep nonlinear network is identified as the global minimum point. Finally, an improved Swish activation function based on batch normalization is proposed, and its performance is evaluated on the MNIST dataset. The experimental results show that the loss of an improved Swish function is lower than that of other activation functions. The prediction accuracy of a deep neural network (DNN) with an improved Swish function is 0.38% more than that of a deep neural network (DNN) with a regular Swish function. For the DNN with the improved Swish function, the mean square error of the prediction for the flatness of cold rolled strip is reduced to 65% of the regular DNN. The accuracy of the improved DNN is up to and higher than the industrial requirements. The shape prediction of the improved DNN will assist and guide the industrial production process, reducing the scrap yield and industrial cost.

Use of Advanced Control Techniques With Virtual Rolling to Improve Threading of the Tandem Cold Mill

The threading of the tandem cold metal rolling mill is a significant function in the control of this process. During the threading process it is important to reduce the excursions in the strip thicknesses and tensions. Additionally, in most cases it is desired by the operational personnel to control the individual mill stand speeds such that, as the head of the strip moves between two adjacent stands, its speed between the two stands is held at the strip speed at the exit of the last stand just before acceleration to run speed. Moreover, it is desired that disturbances in the thickness and the resistance to deformation in the incoming strip are successfully handled by the controller. In this article, we propose a method of improved control for this process that considers all of these requirements. The effectiveness of this method is shown by simulation using data from operating mills.

RESEARCH ON THE VIBRATION OF COLD ROLLING MILL F5 UNDER MULTI-SOURCE EXCITATION

Serious vibration occurred on the F5 stand when producing thin strips on a 1550 cold tandem mill. The field test showed that the dominant frequency of the vibration is 144 Hz, which was close to the natural frequency of the F5 stand. Moreover, there were many excitation frequencies in the strip excitation spectrum and the servovalve pressure spectrum of the screwdown system. To explore the vibration source and suppress the vibration, the industrial field experiment was conducted to concluded that the vibration was affected by the joint excitation of strip steel and the hydraulic screwdown system. The characteristics of different frequency combination acting on the mill were obtained by solving the model of the strip-screwdown excitation. A method was proposed to suppress the vibration. It used the desired excitation combination by adding the vibration suppressor in the control system to eliminate a specific frequency. The satisfactory suppression effect was obtained after the implementation. The research provides a reference for analyzing vibration mechanism of cold tandem mill and expands the method of vibration suppression.

Research on Online Mathematical Models of Tandem Cold Rolling

The tandem cold rolling process control system is an important part of the computer control system of the tandem cold mill coupled pickling line, and it is an important means to ensure the output and quality of cold rolled strip. On-line mathematical models of tandem cold rolling are the premise of formulating rolling rules, setting of rolling mill parameters and calculation of load distribution. They calculate the set values and rolling parameters required by the automation system based on the rolled piece and equipment parameters. Therefore, it is of great practical significance to study the on-line mathematical models of tandem cold rolling and to establish a model of high precision and high value-added products.

Effect of work roll shifting control on edge drop for 6-hi tandem cold mills based on finite element method model

Controlling the profile and edge drop in the cold rolling process is crucial especially in applications involving silicon steel. In non-oriented silicon steel production, the work rolls shifting control is widely applied in 6-high tandem cold mills and the differences of the control characters of different stands have been gradually recognized. However, because of the lack of research on shifting control effect of separate stands and their influence between each other, controlling the edge drop by cooperatively shifting the work rolls of multiple stands is still impossible, so the mills’ capability is not utilized efficiently. In this study, we develop a finite element method (FEM) model to investigate this issue. Based on the results of the FEM model, we conclude that work roll shifting of different stands leads to the independent control of edge drop, obtain the shifting control effect of different stands to their exit, and the attenuation effects by the following stands. Besides, we deduce that the approach to calculating the edge drop control characteristics should be modified to summation equation of the attenuation effects. The results of an experiment involving 6-high tandem cold mills are in agreement with the results of calculation with the FEM model and we demonstrate the high precision of the FEM model and the reliability of the subsequent analysis. Based on the edge drop control characters established, the control model and the cooperation strategy were designed and applied to the practical production, and significant improvements of edge drop and transverse thickness deviation were obtained.

Multi-parameter deep-perception and many-objective autonomous-control of rolling schedule on high speed cold tandem mill

High-speed cold tandem rolling process control system consists of complex mechanical and electrical equipments. The coupling association of these equipments makes multi-objective rolling process complicated to be predicted and controlled. In order to achieve higher prediction precision, a multi-parameter depth perception model is established based on a deep belief network. To get higher control precision in real time, a multi-objective rolling optimization method is introduced, which is supported by many-objective evolutionary algorithm. Five objectives are selected as rolling schedule optimization objective: equal relative power margin, slippage prevent, good flatness, total energy consumption and energy consumption per ton. Simulation results show that many-objective evolutionary algorithm based on decomposition and Gaussian mixture model achieves a set of balance solutions on these objectives. The proposed method could not only predict rolling force and rolling power in real time, but also give the solutions for many-objective reduction schedule.

Optimal Estimation and Feedforward Control of Strip-Longitudinal Hardness for Thickness Hunting Suppression of Tandem Cold Mill Process

Following the recent trend of weight reduction in car industry, producing high quality cold-rolled AHSS (advanced high-strength steel) strip becomes important. Thickness hunting (or fluctuation) problem can be more prominent for this cold-rolled AHSS strip making, which can stem from the non-uniformity of hot-rolled strip and can severely degrade product quality. In this paper, we propose a novel framework to estimate the strip-longitudinal hardness of the TCM (tandem cold mill) process and its feedforward control to substantially reduce the thickness hunting, while fully incorporating the interconnected nature and sensing sparsity of the TCM process. In particular, our estimator consists of the following two complementary loops: 1) fast real-time hardness estimation loop, which optimally fuses the process model and sensing information; and 2) slower constant process-parameter estimation loop via optimization utilizing the nonlinear process model and (stored/measured) sensor data. Efficacy of the proposed estimation and control frameworks are then validated with high-precision TCM process physics simulator.

Design of SCADA for Protection System of Uncoiled DC Motor’s Temperature using PLC ABB AC 800PEC Based on Wonderware Intouch

Continuous Tandem Cold Mill (CTCM) operates many types of DC motor for various processes. The continuity of the DC motor is very important to ensure the automation process are working perfectly and safe. One of the abnormal condition when operating DC motor is overheating at Field winding and Field bearing. Therefore, this research is needed to avoid further damage in the DC motor by designing and implementing protection system of temperature based on PLC (Programmable Logic Controller) ABB AC 800PEC and PT100 sensor. SCADA (Supervisory Control and Data Acquisition) system was implemented so the operator can supervise the motors. When temperature is increasing and higher than the allowed maximum temperature, the system should generate Fast Stop signal to stop every process that have been running at entry section CTCM. The protection system was implemented successfully and generated Fast Stop signal when the Field winding temperature was higher than 100-degree Celsius or when the Field bearing temperature was higher than 75-degree Celsius.

A Mill Set-up Model Using a Multi-output Regression Tree for a Tandem Cold Mill Producing Stainless Steel

A Mill Set-up Model Using a Multi-output Regression Tree for a Tandem Cold Mill Producing Stainless Steel

Practical Issues in the Design of Wireless Sensors Supplied by Energy Harvesting Thermoelectric Generators

The use of energy harvesting for supplying wireless sensors becomes a new market opportunity. During last years, new low power transmitters, and also power conversion ICs specifically designed for energy harvesting, have become commercially available. However, as any other power supply circuit, the specific load behavior affects to the power converter, doing that just joining the two parts takes to a nonfunctional device. In this paper, we will measure experimentally the transmitter current of some technologies, for the several sensor states. Some practical issues that affect directly the sensor design will be shown. With this information, some required modifications in the power stage will be proposed. A complete temperature sensor design and assembly is showed. The sensor has been tested in a tandem cold mill, and several experimental results are included.

A novel approach to improve the computing accuracy of rolling force and forward slip

ABSTRACTIn cold strip rolling control system, rolling force and forward slip are the prerequisites for the model setting calculation, and the deformation resistance and friction coefficient are the main parameters that affect their predictions. A new method based on objective function is first proposed in this paper to improve the calculation accuracy of rolling force and forward slip, and the deformation resistance and friction coefficient are taken as optimisation variables. Using the multi-population co-evolutionary algorithm to solve the objective function, the required rolling force and forward slip are obtained. The pre-set values of rolling force and roller line speed are compared with the actual measured ones in a 1450 mm five-stand tandem cold mill and other researcher’s method. Results show that the calculated values are in fair agreements with the on-line measured ones, and the thickness and flatness accuracy of the final product are improved.

A novel approach for the rolling force calculation of cold rolled sheet

The rolling force model was the core factor for the control system of the cold rolled sheet, the prediction accuracy affect the final flatness and the strip thickness directly. A novel approach for the rolling force prediction of cold rolled sheet was first proposed based on the plastic mechanics, in which the cylindrical velocity field was used to analyze the metal flow in the deformation region by the upper bound analysis in this paper. The analysis solution of rolling torque, rolling force and stress state coefficient are obtained by minimizing the total power which contain the internal plastic power, frictional power, shear power and tense power. Moreover, the effects of frictional factor, reduction ratio and the tense on the location of neutral point and stress state coefficient are discussed, respectively, and the validity of the proposed model was verified by comparing with the traditional models. The calculation process was programed and applied in the control system of one 1450 mm cold tandem mill successfully, the prediction results was in good agreement with the actual measured ones, and deviation proportion in the range of ±10.0% reached 97.3%, it can meet the requirements of the control system in cold rolling process.

Dynamic Optimization Model of Flatness Target Curve Based on Hybrid Intelligent Algorithm

By the intelligent strategy of dynamic optimization in flatness target curve, the potential of the flatness control system can be completely fulfilled and the satisfying strip flatness can be speedily obtained. The traditional intervention pattern is static, open‐loop, non‐intelligent. In this paper, a new dynamic adjustment model of flatness target curve has been designed, by which the initial setpoint can be real‐timely regulated. The closed‐loop control system, equipped with the function of intelligent optimization and dynamic regulation, has been developed. A hybrid intelligent algorithm called ZOGE, in which both the searching definiteness and randomness are taken into account and the multipoint searching and single‐point searching are simultaneously carried through, has been proposed. The equivalent factor of flatness target curve has been optimized by function module HYBALO, which is developed on the basis of the hybrid intelligent algorithm and is operated on CFC configuration language in SIMATIC TDC controller. The testing in the field has been conducted through a 1450 mm 5‐stand tandem cold mill. The preliminary finding from the main results of testing in the field is reported: by means of the intelligent compensation model of flatness target curve, the content flatness quality of strip with thin thickness in slow rolling speed is effectively guaranteed. The maximum compensation efficiency of speed is 72.19%. The maximum compensation efficiency of thickness is 98.37%. The ability of eliminating strip flatness defect in dynamic regulation mode of flatness target curve is more powerful than the ability of eliminating strip flatness defect in conventional regulation mode.