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In order to meet the shape control requirements of “dead flat” transverse thickness profile of electrical steel sheet in cold rolling process, the 3D finite element model (FEM) for roll stacks and strip of 6-high tandem cold rolling mills (TCMs) was built with the developed Edge Drop Control Work Rolls for Non-shifting (EDW-N). The efficiency curves of the work roll bending (WRB), the intermediate roll bending (IRB), and the intermediate roll shifting (IRS) in cold rolling process are obtained for transverse thickness profile control performance. The control strategy of multi-stand and multi-variable profile and flatness control actuators, i.e., WRB, IRB, and IRS of stands 1 ~ 5 in 6-high TCMs is proposed based on the GA-PSO hybrid algorithm with better optimization ability. The results show that the control strategy can fully exploit the shape control ability and achieve the high precision control for transverse thickness profile of 6-high TCMs. The industrial application on the production gives remarkable results that the rate of the measured strip crown less than 7 μm increased from 38.58 to 67.74% for electrical steel sheet in the 1420-mm 6-high TCMs. The control strategy has applied to the production successfully.

This paper introduces a novel method for enhancing fault classification and diagnosis in dynamic nonlinear processes. The method focuses on dynamic feature extraction within multivariate time series data and utilizes dynamic reconstruction errors to augment the feature set. A fault classification procedure is then developed, using the weighted maximum scatter difference (WMSD) dimensionality reduction criterion and quadratic discriminant analysis (QDA) classifier. This method addresses the challenge of high-dimensional, sample-limited fault classification, offering early diagnosis capabilities for online samples with smaller amplitudes than the training set. Validation is conducted using a cold rolling mill simulation model, with performance compared to classical methods like linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD). The results demonstrate the superiority of the proposed method for reliable industrial process monitoring and fault diagnosis.

The ridge buckle defect is a perennial challenge in the Steel Industries. Its sporadic appearance at the cold rolling mill (CRM) precipitates the degradation of cold-rolled products. It is unequivocally established that the genesis of this defect lies within the hot strip mill (HSM), manifesting during the cold rolling process subsequent to annealing and skin-pass rolling. In spite of several research attempts, conclusive evidence to definitively resolve this issue remains elusive. This study endeavours to analyse the effect of ramifications of thickness variation in the transfer bar (TB) from the roughing mill, directly fed into the finishing stands of the HSM, on roll wear and strip profile. We hypothesize that this variation may predispose the TB to ridge buckle defects. To investigate this, the study conducts a meticulous statistical and experimental inquiry into the impact of thickness variation in the TB from the roughing mill on the wear of work rolls, which could be a catalyst for ridge buckle defects. The analysis unequivocally corroborates that the incidence of ridge defects is intricately intertwined with the wear profile of the work rolls of last roughing stand (i.e., R5), aligning with the prevailing production conditions within actual plant operations. Highlights Effect of wedge of transfer-bar on ridge formation of cold-rolled strip has been explored here. Microstructural, mechanical, and surface topography characterizations of the ridge defects as well as non-ridged portions of the cold rolled strips have been carried out. This research reveals that variation in the thickness of transfer-bar promotes ridge formation in cold-rolled strip. Graphical Abstract

The metal manufacturing industry employs the reversible cold rolling mill, which is a machine used to process and shape various metal products such as steel sheets, aluminum sheets, and copper sheets. High accuracy control of web velocity and web tension is essential in the manufacturing process for preventing the web from bending or breaking during the entire manufacturing process. In this work, we introduce a control law design method using PI control with unknown parameters for the web winding system to ensure that the final product will not be affected by deformation or breakage. In the first step of the adaptive backstepping procedure, the integral action is obtained by adding the integral of the tracking error to the error considered. The stability of the control design is ensured by the Lyapunov stability theorem. It verifies that the trajectory dynamics are asymptotically stable. To illustrate the effectiveness and performance of the proposed controllers, simulation studies using the MATLAB/Simulink environment are presented.

In order to investigate the random vibration characteristics of a cold rolling mill under the excitation of different morphologies on the strip surface and to study the spatial distribution of vibration amplitude inside the key components of the cold rolling mill. Firstly, the 3D scanning equipment was used to obtain the surface morphology of continuous casting slabs, and then reverse engineering was used to obtain the height data of vibration marks on the slabs, and then the Gaussian distribution random function was used to carry out the data regression and the random vibration analysis of the whole model of the cold rolling mill, and finally the distribution of vibration amplitude inside the key components of the cold rolling mill was observed using the slicing method. The 3D scanning equipment was used to collect the surface morphology of the slab and the height data of the vibration marks on the surface of the slab were obtained by reverse engineering, and the random function Gaussian distribution method was used to regress the surface morphology of the continuous casting slab, and the sample collection of different morphologies of the strip surface was realized. The analysis process of random vibration characteristics of cold continuous rolling mill was sorted out, and it was found that the maximum value of random vibration displacement was on the transmission side, which verified that the vibration characteristics of cold continuous rolling mill could be better characterized by random vibration characteristic analysis. The slicing method observes the internal vibration amplitude distribution of the key components of the cold rolling mill, showing the phenomenon of “small in the middle and large at the end”. The application of the random function of Gaussian distribution provides a new method for the expression of slab morphology, and also provides a data basis for excitation of random vibration in cold continuous rolling mill. The application of the slicing method provides a new idea for analyzing the internal vibration state of key components of the cold continuous rolling mill.

In the steelmaking industry, the demand and expectations from the customers are more stringent than ever, primarily owing to increased competition and stressed margins. Any steel coil with holes on the surface passed to the customer can potentially result in a severe complaint and a dent in the company’s reputation of being a quality product supplier. In the cold-rolling mills (CRM), supplier companies roll premium-grade steel strip products for several industry sectors including automobile customers. Manual and other pre-existing detection techniques of smaller miniature size holes on the strip moving with the high line speed is highly unreliable. Passing an undetected hole to the customer has serious consequences as it may cause damage to the costly equipment like die and can result in rejection of a complete BIW (body in white). To overcome this challenge, we propose an image processing-based miniature size hole detection system, which helps CRM (cold-rolling mill) to detect the material with pinholes in-process and prevents them from reaching the customers. Equipped with an innovative imaging setup including blue light and viewing angle enhancements, our proposed system surpasses the pre-existing hole detection technologies by a huge margin. This system has been developed and tested in a customer-facing line.

The 6-high continuously variable crown (6-h CVC) cold rolling mill shows limited capability to control coupled edge and center waves for both narrow strip and ultra-wide strip production. In order to solve this problem, an integrated three-dimensional (3D) elastic-plastic finite element model (FEM) of rolls and strip is built to calculate the effect functions in consideration of work roll bending (WRB), intermediate roll bending (IMRB), and CVC intermediate roll shifting (IMRS) with different strip widths. A set of orthogonal vectors which is defined as eigenvectors is proposed to analyze the similarities and the complementarities of the effect functions. It is applied to study the flatness control characteristics of the cold rolling mill. Based on the analysis of flatness stress characteristics of different strip widths in the production, it is found that the similarities between the flatness stress and the eigenvectors of different strip widths are relative low. The flatness defects are difficult to be eliminated. From the relationship between IMRS and strip widths, a segmented CVC intermediate roll contour is then proposed and experimented in an industrial production. The proportion of coupled edge and center waves is decreased by 15.2%, and the overall flatness is reduced by 0.7 IU.

The cold rolling mills are complex electro-hydro-mechanical systems in which vibrations are usually detected as issues during production process. In the present work, the vibrations with frequencies of 80Hz were found at top of the rolling mill and the pressure behind servo valve during the production process. In order to understand the vibration mechanism and to explore the measurements for vibration suppression, the dynamic models were proposed to describe valve spool, 8-DOF cold rolling mill, and hydraulic system based on the dynamic characteristics of servo-valve. The analytical solutions and numerical solutions were obtained for the vibration rules for the valve spool displacement and the output flow rate under different working conditions. Moreover, the influence of dynamic characteristics of servo-valve on the vibrations and optimization of the servo-valve were discussed. The results suggest that the dynamic characteristics of servo-valve have a significant influence on the hydro-mechanical coupled vibration of rolling mill and the vibrations can be dampened by improving the dynamic characteristics of rolling mill. This work is expected to provide a new perspective to suppress the hydro-mechanical coupled vibrations.

The basic control model of longitudinal thickness variability based on the graphic solution to the system of two equations is improved. The model allows regulating the longitudinal profile at skin rolling of a strip on a cold-rolling mill taking into account the most important technological parameters affecting the cold rolling force. Representation of this system as differential equations confirms the original correctness of the graphic solution, allows determining the stiffness modulus of the rolled strip, and choosing the control actions for the technological parameters of the skin rolling process. The reliability of this model is checked by comparing the profile diagrams of the calculated and measured mean values of the longitudinal thickness variability at cold rolling of strips on a skin rolling mill 2000 of Severstal Company. It is shown that an increase in the head and trail specific tensions on a skin rolling mill allows reducing the oscillations of the thickness over the entire area of the rolled strip to the required tolerance from the nominal thickness.

During tandem cold rolling mill process, strip tearing reduces production rate, damages the rollers, and consequently decreases efficiency of production. Predicting and postponing of this phenomenon leads to less expensive trial and errors in rolling industries. In this research first, DIN1623 St12 steel which is frequently applied in metal forming industries and also Bao–Wierzbicki ductile damage criterion is selected. Then, six curve fitting methods are employed to calibrate the material and are presented in 2D space of equivalent plastic strain to fracture and stress triaxiality. Finally, the achieved fracture loci are validated by comparing corresponding simulation results with experimental tests and the best curve fitting method with aims of high accuracy for tracking the strip tearing in a tandem cold rolling mill process and fewer numbers of required tests is revealed. Eventually, due to engaging this innovative approach, it is possible to trace the strip tearing in tandem cold rolling mill process by performing only two simple tensile tests. Therefore, it is concluded that strip tearing phenomenon can be precisely predicted in tandem cold rolling mill processes by a special focus on calibration of the Bao–Wierzbicki damage criterion in the range of low positive stress triaxiality which causes less number of needed tests.