Quantitative Evaluation Method of Shape Indicator for Cold-Rolled Strip

Yang, Lipo; Yu, Bing-qiang; Yu, Hua; Du, Changcheng

doi:10.1016/s1006-706x(14)60172-2

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…With the development of cold rolling technology and shape theories, some types of comple waves were not to be done by some single regulation but the coordinated regulation. In the practical rolling process, different control strategies were needed to be done according to the characteristics of different control methods for achieving the best strip shape control, as shown in Figure b.…”

Section: Process Analysis Of Strip Shape Controlmentioning

confidence: 99%

Intelligent Shape Regulation Cooperative Model of Cold Rolling Strip and Its Application

Yang

Wang

et al. 2017

steel research int.

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A new strip shape control model is established to achieve the synchronizing control of complex shape defects, which can not only takes advantage of the mechanism model's strong analysis ability, but also combines with the fast online calculation function of intelligent model to reduce the poor efficiency regulation. Firstly, the dynamic target strip shape is expressed with the Legendre polynomial contained various components to describe all kinds of online shape targets, so it is easier to compare the shape control effect. Secondly, with the dynamic influence matrix and the efficiency function, some different control methods can be tightly combined in one regulation cycle to carry out the synchronous parallel control and the serial relay regulation, respectively. At the same time, by the DE‐ELM method, the intelligent shape control model can play an important role to improve the regulation efficiency of the online strip shape. On the other hand, the collaboration regulation model can make full use of all the effectiveness of each control methods according to their respective characteristics, so that the high precision of the strip shape control is able to be obtained.

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Section: Process Analysis Of Strip Shape Controlmentioning

confidence: 99%

Intelligent Shape Regulation Cooperative Model of Cold Rolling Strip and Its Application

Yang

Wang

et al. 2017

steel research int.

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“…The influence of sensor reliability on the shape detection signal has rarely been investigated. Yang et al [ 4 , 5 , 6 ] determined the influence of zero residual voltage and the shapemeter roll deflection on the sensor work reliability. However, the influence of the sensor reliability, resulting from the sensor size parameters induced by the temperature and tension of the strip, remains unexplored.…”

Section: Introductionmentioning

confidence: 99%

Reliability Evaluation and Robust Design of a Sensor in an Entire Roller-Embedded Shapemeter

Cui

Zhang

et al. 2018

Sensors

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The intermittence of the shape detection signal associated with an entire roller-embedded shapemeter roll, used in a seven-pass cold reversible rolling process, is considered. A transient interference at the sensor top surface and the distance between the sensor top surface and the roll outer surface are developed, and a sensor reliability evaluation model is derived. The reliability of the sensor is evaluated via the random perturbation method, and the reliability sensitivity of design variables is proposed. The analysis reveals that the reliability is smallest in the third rolling pass. Of the design variables considered, the initial interference exhibits the largest reliability sensitivity and has the greatest influence on the sensor reliability. A reliability robust design model of the initial interference is therefore developed. A new shapemeter roll is fabricated and tested in a 1050 reversible cold rolling mill. The test results are consistent with the theoretical results, thereby validating the proposed model. The selection of an appropriate initial interference provides an important means of overcoming the adverse effects associated with the thermal deformation of sensor contact surfaces.

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Development of an Online Warping Detection System for Cold-Rolled Thin Strip Steel

Wen

Lin

et al. 2023

JOM

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Quantitative Evaluation Method of Shape Indicator for Cold-Rolled Strip

Cited by 4 publications

References 12 publications

Intelligent Shape Regulation Cooperative Model of Cold Rolling Strip and Its Application

Intelligent Shape Regulation Cooperative Model of Cold Rolling Strip and Its Application

Reliability Evaluation and Robust Design of a Sensor in an Entire Roller-Embedded Shapemeter

Development of an Online Warping Detection System for Cold-Rolled Thin Strip Steel

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