Roll Eccentricity Research Articles

Roll Eccentricity Detection and Application Based on SFT and Regional DFT.

Roll eccentricity disturbance is a high-frequency periodic change signal caused by the irregular shape of the roll and roll bearing, which is difficult to identify and affects the periodic deviation of the exit thickness of the strip. To achieve rapid identification of the source and a mathematical model of roll eccentricity signals, a sparse Fourier transform (SFT) and regional DFT method for roll eccentricity signal recognition and detection was proposed. This method utilizes SFT to calculate the signal FFT more quickly based on the sparsity of the signal frequency domain. Under the premise of knowing the roll diameter, the signal frequency spectrum is identified online, the amplitude and phase are identified through regional DFT, and the eccentricity disturbance is compensated on site. The simulation results show that this method can accurately identify the source of roll disturbance, quickly update and replace the problematic rolls, and improve the online recognition efficiency by more than 3000 times. This method has good results in online detection and recognition of roll eccentricity signals, greatly improving engineering application efficiency, and ultimately achieving the goal of improving the accuracy of strip outlet thickness.

Liquid Core Detection and Strand Condition Monitoring in a Continuous Caster Using Optical Fiber

Real-time monitoring of the liquid core position during the continuous casting of steel has been demonstrated using low-cost distributed optical-fiber-based strain sensors. These sensors were installed on the containment roll support structures in the segments of a production continuous caster to detect the position of the solid-liquid interface and monitor the strand condition during the continuous casting. Distributed Fiber Bragg Grating sensors (FBGs) were used in this work to monitor strain at six roll positions in the caster. The sensor performance was first validated by comparing optical strain measurements with conventional strain gauge measurements in the lab. Next, optical strain measurements were performed on an isolated caster segment in a segment maintenance facility using hydraulic jacks to simulate the presence of a liquid core under the roll. Finally, the sensors were evaluated during caster operation. The sensors successfully detected the load increase associated with the presence of a liquid core under each instrumented roll location. Incidents of bulging and roll eccentricity were also detected using frequency analysis of the optical strain signal. The liquid core position measurements were compared using predictions from computer models (digital twins) in use at the production site. The measurements were in good agreement with the model predictions, with a few exceptions. Under certain transient caster operating conditions, such as spraying practice changes and SEN exchanges, the model predictions deviated slightly from the liquid core position determined from strain measurements.

Roll Eccentricity Signal Detection and Its Engineering Application Based on SFFT-IAA

The roll eccentricity signal is a weak and complex periodic signal that is difficult to be identified. To improve the detection accuracy of the roll eccentricity signal and to compensate effectively, this study proposed a roll eccentricity signal detection method by combining the sparse fast Fourier transform (SFFT) and the iterative adaptive approach (IAA). The proposed method can rapidly determine the frequency range of the roll eccentricity signal by using the SFFT. Then, it divides the frequency range into several small frequency bands. In each small frequency band, the frequency, amplitude, and phase angle of each harmonic component of the roll eccentricity signal were estimated by using IAA. The simulation results show that the proposed method can find all frequency components, and the frequency estimation accuracy is higher than 99.88%. Finally, the engineering application of this method and the eccentricity compensation control were investigated. In engineering applications, the proposed method can reduce the thickness fluctuation of the finished strip by 89.2%, and the product quality is improved significantly. The simulation results and engineering experiments show that the proposed method has an excellent effect on detecting and compensating roll eccentricity signals.

Roll eccentricity extraction and compensation based on MPSO-WTD and ITD.

To meet the high thickness accuracy requirements in cold-rolling processes, a roll eccentricity signal extraction method based on modified particle swarm optimization and wavelet threshold denoising (MPSO-WTD) with intrinsic time-scale decomposition (ITD) is proposed. The strong denoising ability of the wavelet is combined with the decomposition and recognition attributes of ITD for non-stationary signals. Periodic disturbances in strip thickness caused by roll eccentricity are actively compensated. First, the wavelet is used to denoise the signal and the MPSO algorithm is applied to determine a rational threshold and improve the calculation efficiency. Then, the denoised signal is decomposed into proper rotational components (PRCs) using the ITD method, and an appropriate PRC component representing the eccentricity signal is extracted. Finally, the eccentricity compensation signal is applied in the automatic gauge control (AGC) system of the cold rolling mill. During the rolling process, the rolling speed is not constant and will directly affect the frequency of the roll eccentricity signal. To solve this problem, an encoder is installed at the end of the roll and the compensation frequency of the roller eccentricity signal is determined in the roller eccentricity compensation system according to the pulse number output. The results of simulations and experiments show that roll eccentricity signals extracted using the proposed method can effectively remove the influence of interference signals. An average improvement of 62.3% in the roll eccentricity compensation effect was achieved under the stable rolling condition in the finishing rolling stage.

Effect of Front Top Roll Eccentricity in Ring Spinning on Yarn Regularity and Imperfections.(Dept.T)

The study reported in this paper concerns the influences of front top roll eccentricity in ring spinning machine), loading the top arm, pressure distribution on top arm through changing pin position and delivery sp eed on yarn irregularity and imperfections (thin, thick places and neps). The results show that: roll eccentricity has a positive effect on yarn irregularity and imperfections. This effect increases by increasing delivery speed. Loading the top arm of 2.3 bar with first pin position or 1.7 bar at third pin position reduced thin, thick places and nep s at the higher delivery speed. Also pressure distribution (or pin position) influences yarn irregularity and imperfections at the higher delivery speed.

A Robust Data-Driven Fault Detection Approach for Rolling Mills With Unknown Roll Eccentricity

This brief proposes a robust subspace-aided fault detection approach for rolling mill processes with roll eccentricity. The novelty of this brief relies on the closed-loop identification of the so-called data-driven realization of the stable kernel representation (SKR) of the rolling mill process. In order to ensure an accurate and robust closed-loop identification, the mappings among the closed-loop process data and the unknown disturbance are analyzed analytically based on the process model, which play essential roles in the data-driven realizations and designs. By determining the kernel subspace of the rolling mill process, a robust data-driven fault detection approach is derived and a disturbance-decoupled residual signal can be obtained. The effectiveness of the proposed approach in comparison to conventional data-driven designs is demonstrated through case studies on a rolling mill benchmark process.

Control Performance Monitoring of State-Dependent Nonlinear Processes

This paper presents a novel approach to monitor control performance of nonlinear processes that can be described as state-dependent models (SDMs). A discrete Kalman filter (KF) is established to estimate the SDM parameters. A covariance control formulation is introduced to split the system closed-loop variance/covariance into two terms, one term to account for the minimum expected quadratic loss bound (equivalent to the minimum variance performance bound but in state space formulation), and another to account for performance deviations from the minimum variance bound. Simulation studies have been conducted on several nonlinear process systems including a cold rolling mill model with roll eccentricity and a steel making system with real time oxyfuel slab reheating furnace control data. The case study results demonstrate the computational efficiency of the proposed strategy in real time monitoring and control of systems with fast, nonlinear and time-varying dynamics.

롤투롤 시스템에서 플렉시블 소재에 인가된 장력과 분사 높이가 액적 접촉각에 미치는 영향

This study proposes a method for identifying correlations between tension and drop height for sessile droplets in a roll-toroll processing system. The effect of tension and drop height on the contact angle of a sessile droplet is presented. Design of experiment (DOE) methodology and statistical analysis are used to define a correlation between the process parameters. The contact angle is decreased while increasing tension and drop height. The influence of the tension is less significant on the contact angle compared with the effect of the drop height. However, tension should be considered as a major parameter because it is not easy to fix with roll eccentricity and compensating speed of the driven roll. The results of this study show that the effect of tension on the contact angle of a sessile droplet is more important than drop height because the drop height is fixed when the process systems are determined.

Online Monitoring System Design for Roll Eccentricity in Rolling Mills

This paper deals with the parameter estimation and online monitoring of roll eccentricity in rolling mills. Roll-eccentricity-induced disturbances can result in strip thickness deviation and product quality degradation, and a conventional control strategy cannot regulate this kind of periodic disturbances due to its complex characteristics. For the purpose of product quality assessment and monitoring, a performance indicator based on product expectations or the empirical value of quality-related process variables, which can be quantitatively visualized with four zones, is proposed in the high level. In the low level, the key parameters of roll eccentricity are estimated in real time using an adaptive observer for frequency estimation and an adaptive algorithm for amplitude and phase estimation. The performance and effectiveness of the proposed eccentricity monitoring system are demonstrated through a case study of a cold rolling mill from industrial fields.

대면적 탄소나노튜브 / 은나노와이어 투명전극필름 롤투롤 연속생산시스템

A roll-to-roll (R2R) continuous manufacturing system for a carbon-nanotube (CNT)-/silvernanowire (AgNW)- based large-area transparent conductive film was introduced in this study. The systemic guidelines of the R2R slot-die coating process including roll eccentricity, wrap angle, pump accuracy, and blower influence were discussed. To simulate the coating phenomenon, we investigated the governing parameters of the coating process by incorporating the estimated relative thickness that was defined by combining the viscocapillary model and volume model. By using experimental and mathematical approaches, an excellent transparent conductive layer with a 40 Ω/□ sheet resistance and 88 % transmittance was obtained; moreover, a dimensionless number identifies the correlation between the transparent conductive film and the anti-reflection film.

Analysis of Roll Eccentricity Signal in Strip Cold Rolling Process Based on Order Tracking

Aim at the problem of roll eccentricity in measuring on line and presenting accuracy, an new effective solution is provided. According to the theory of plate and strip rolling, the roll eccentricity online soft measurement model is established, through the collected pressing cylinder displacement, rolling force, export plate thickness data during the rolling process, the roll eccentricity can be estimated. In order to solve the roll eccentricity signal frequency and cycle diversification when the rolling speed changes, the order tracking technique is applied, the time marks of same angle sampling are calculated, and the values of resample in angle domain are calculated by Lagrange interpolation method. The time sequence of rolling process data is translated into angle domain sequence. And the mismatching of data due to the lag of thickness signal is solved by moving in angle domain. The signal of roll eccentricity is analysis and extracted by wavelet filtering and coherence time average method, which is the basement work to compensate the roll eccentricity effectively.

Restraint Strategy for Chaos in Auto Gauge Control System

In this paper, conditions of the chaos in auto gauge control system are suggested and proved on the basis of the roll eccentricity model. It is proposed that the eccentricity disturbance of roll may cause chaotic phenomena in the rolling process. By analyzing four kinds of expandable and shrinkable factors of variable universe fuzzy controller, it is suggested that the contradiction between fuzzy control rules and control accuracy can be solved effectively by HACO-VUFC meth- od. Simulation shows that the product quality can be improved by chaos inhibition.

Modeling and Analysis of Interstand Tension Control in 6-high Tandem Cold Rolling Mill

The interstand tension control is one of the most important ways to meet tight tolerances for strip product quality during tandem cold rolling process. Using coordinate analysis and parabolic approximation for the mass flow balance principle, the strip velocities eliminating the use of forward slips and backward slips were calculated. In order to reduce the effect of roll eccentricity on the tension measurement, a filter based on bilinear transformation was designed. Applying a first-order Taylor series approximation, the transfer function matrix model of interstand tension stress was derived. The actual measurements on-site and the final calculation results showed that the established model had high calculation accuracy and was beneficial for interstand tension control of tandem cold rolling process.

Application of Dynamic Deadband Eccentricity Filter in GM-AGC System

The problem of roll eccentricity has become one of important factors to affect the quality of strips as downstream industries require improvement of the strip quality. Reducing thickness control precision as little as possible is incompatible with restraining roll eccentricity perturbations on the requirement of the deadband size for the deadband drift method (DDM) with fixed deadband width. Therefore, the GM-AGC system in hot finishing mill of an aluminum plant uses the dynamic deadband eccentricity filter (DDEF) whose deadband width varies with the amplitude of the roll eccentricity signal. The operating principle of DDEF was introduced according to the characteristic of roll eccentricity signal. Based on the theory of DDEF, simulation was carried out. Comparing with DDM, the simulation result shows that DDEF can keep a balance between less lowering thickness control precision and restraining roll eccentricity perturbations on the requirement of the deadband size. Moreover, the deadband width of DDEF is capable to fit the variations in the frequency and amplitude of the synthetic roll eccentricity signal to restrain the misoperation of GM-AGC system.

Strip Thickness Control of Cold Rolling Mill with Roll Eccentricity Compensation by Using Fuzzy Neural Network

In rolling mill, the accuracy and quality of the strip exit thickness are very important factors. To realize high accuracy in the strip exit thickness, the Automatic Gauge Control (AGC) system is used. Because of roll eccentricity in backup rolls, the exit thickness deviates periodically. In this paper, we design PI controller in outer loop for the strip exit thickness while PD controller is used in inner loop for the work roll actuator position. Also, in order to reduce the periodic thickness deviation, we propose roll eccentricity compensation by using Fuzzy Neural Network with online tuning. Simulink model for the overall system has been implemented using MATLAB/SIMULINK software. The simulation results show the effectiveness of the proposed control.

Robust Backstepping Control for Cold Rolling Main Drive System with Nonlinear Uncertainties

The nonlinear model of main drive system in cold rolling process, which considers the influence with parameter uncertainties such as clearance and variable friction coefficient, as well as external disturbance by roll eccentricity and variation of strip material quality, is built. By transformation, the lower triangular structure form of main drive system is obtained. The backstepping algorithm based on signal compensation is proposed to design a linear time-invariant (LTI) robust controller, including a nominal controller and a robust compensator. A comparison with PI controller shows that the controller has better disturbance attenuation performance and tracking behaviors. Meanwhile, according to its LTI characteristic, the robust controller can be realized easily; therefore it is also appropriated to high speed dynamic rolling process.

The Improvement and Simulation on the Dynamic Model of Hydraulic AGC System

The paper uses the object-oriented modeling method to analysis the hydraulic AGC system and the operation mechanism about a strip mill. It discusses the Coulomb force and roll eccentricity which usually were ignored on rolling process. And improves the mathematical model that reflect the actual AGC system. By simulation, we compared it with the actual rolling process and verified the correction of the mathematical model. And, it will make the good foundation for on-the-spot practical application.

Roll Eccentricity Phase Identification System

Roll eccentricity is widespread in the strip mill, has cyclical impact on strip thickness, so disturbance compensation is required to improve the product quality. The key step of disturbance compensation is to obtain reliable roll eccentricity signal. Existing direct measurements of roll eccentricity signal method requires special equipments with high precision but not practical enough. There are few detection methods which including rolling velocity. Roll eccentricity signal is difficult to directly measured, should fuse many kinds of detectable signal to be extracted through the data analysis which includes rolling force, roll gap, incoming thickness of rolled piece, exit thickness, tension, and so on. This paper puts the four high mill as an object, according to the influence of the main factors of roll eccentricity ——backup-roll eccentricity for analysis, develops a Roll Eccentricity Phase Identification System. This system extracts from amplitude of eccentricity signal, combines eccentricity signal’s frequency with phase through roll segmentation marker integrating rolling speed, according to its cyclical change law to achieve the signal calibration by testing amplitude characteristics to determine the phase of roll eccentricity of the current rolling area. After determining the signal phase, detect the phase of eccentricity signal according to integration of rolling speed, and through phase detection to ensure the reliability of the detectable phase. This system is verified by the experiment in four high mill, the results show that the method of phase detection of eccentricity is effective, it provides a simple and effective new way for the phase extraction of roll eccentricity signal, and can used in similar condition.

Roll Eccentricity Extraction Method Based on Comprehensive Signal Processing

In modern steel production, strip products account for more than half of the total output. Roll eccentricity is ubiquitous in strip mills, which has a periodic impact on the strip thickness difference. Roll eccentricity compensation is an important part of the automatic gauge control system. Most roll eccentricity compensations extract the roll eccentricity based on the frequency domain analysis of the rolling force. It is difficult to ensure measurement precision of roll eccentricity due to the complexity of interference of the rolling force, therefore the compensation accuracy is difficult to ensure. The roll eccentricity extraction method, based on comprehensive signal processing, was introduced in this paper combined with engineering practice. The roll eccentricity was comprehensively calculated by thickness gauge and other signals that have been delayed; the roll phases were calculated by the roll rotational displacement; and finally, the roll eccentric fluctuation of the upper backup roll and lower backup roll were extracted. The roll eccentricity could be predicted by calculating roll eccentric fluctuations and phases, in order to provide the basis for accurate compensation. According to the comparison with roll eccentricity extracted by the frequency domain analysis of the rolling force, the roll eccentricity obtained by the roll eccentricity extraction method, based on comprehensive signal processing, is more accurate. It provides a reliable basis for roll eccentricity compensation in order to improve the accuracy of the thickness of the strip products.

Frequency-adaptive Backup-Roll Eccentricity Compensation with Force Feedback

In this paper we present a novel nonlinear adaptive control algorithm aiming at improving the thickness performances of metal strip rolling mills by actively compensating the periodic disturbances due to the eccentricity of the rolls. The main feature of the proposed Roll Eccentricity Compensation method consists in the capability of estimating the frequency of the disturbance without the need to install proximity sensors for synchronization. The proposed compensation scheme relies on a generalized nonlinear phase-locked loop, whose parameters are adapted online to achieve asymptotic cancellation of the unknown perturbation. The local asymptotic stability of the closed-loop system in presence of model uncertainty is proven by a two-time scale averaging analysis.