EFFECT OF ASYMMETRICAL STAND STIFFNESS ON HOT ROLLED STRIP SHAPE

2008 ◽  
Vol 22 (31n32) ◽  
pp. 5734-5739 ◽  
Author(s):  
DIANYAO GONG ◽  
JIANZHONG XU ◽  
ZHENGYI JIANG ◽  
XIAOMING ZHANG ◽  
XIANGHUA LIU ◽  
...  
Keyword(s):  
Rolling Mill ◽  
Deformation Analysis ◽  
Rolled Strip ◽  
Force Distribution ◽  
Influence Coefficient ◽  
Single Wave ◽  
Hot Rolled Strip ◽  
Strip Shape ◽  
Roll Deformation ◽  
Hot Rolled

The difference of elastic springs between the operating side (OS) and driving side (DS) of rolling mill has a significant influence on the strip shape not just the strip thickness. Based on the slit beam and roll deformation theories, the roll force distribution was analysed considering the asymmetric stiffness of the OS and DS of rolling mill, and the work roll and backup roll deformation equations were deduced respectively, and the thickness distribution in lateral direction of the hot rolled strip at exit was discussed. Using the roll elastic deformation analysis software which was developed previously based on the influence coefficient method, the roll flattening distribution, roll pressure distribution and the rolling force distribution caused by the asymmetric stand stiffness were calculated and analysed, and the exit strip profile of the rolling mill was also presented. The relationship between the mill stiffness difference and the strip wedge shape or single wave was obtained. Effect of the upstream asymmetric mill on strip crown and flatness of the downstream stands was discussed.

EFFECT OF ASYMMETRICAL STAND STIFFNESS ON HOT ROLLED STRIP SHAPE

2009 ◽  
Author(s):  
DIANYAO GONG ◽  
JIANZHONG XU ◽  
ZHENGYI JIANG ◽  
XIAOMING ZHANG ◽  
XIANGHUA LIU ◽  
...  
Keyword(s):  
Rolled Strip ◽  
Hot Rolled Strip ◽  
Strip Shape ◽  
Hot Rolled

Research on Abrasion Mechanism of Working Roll and Strategies of Anti-Wear in Tension Leveler

2014 ◽  
Vol 577 ◽  
pp. 174-177
Author(s):  
Bing Chen ◽  
Ming Cheng He ◽  
Hai Hai Lin
Keyword(s):  
Heat Treatment ◽  
Abrasive Wear ◽  
Rolling Mill ◽  
Working Condition ◽  
Main Type ◽  
Surface Hardness ◽  
Rolled Strip ◽  
Wear Rates ◽  
Hot Rolled Strip ◽  
Hot Rolled

Combining with both working condition of working roll in tension leveler and wear classification, this paper maintains that abrasive wear is the main type of working roll’s abrasion, and states that shape defects of hot rolled strip is the main cause of the abnormal abrasion of working roll, and concludes that to reduce the wear of working roll relying solely on technology of tension leveling has its limits. So, combining with the materials of working roll in tension leveler and rolling mill, the surface hardness and the wear rates of different materials after heat treatment are experimentally analyzed to provide a theoretical guidance for the further improvement of working roll’s materials.

Analyse and Control Research about the Cause of Shape Defects on Hot-Rolled Strip Steel

2013 ◽  
Vol 712-715 ◽  
pp. 725-728
Author(s):  
Xin Cheng Li ◽  
Tao Jiang ◽  
Wei Xing Zhu ◽  
Jian Hua He ◽  
Ai Qun Li ◽  
...  
Keyword(s):  
Morphological Characteristics ◽  
Work Roll ◽  
Rolled Plate ◽  
Rolled Strip ◽  
Strip Steel ◽  
Hot Rolled Strip ◽  
Strip Shape ◽  
Control Research ◽  
Hot Rolled ◽  
Roll Shape

Strip shape defects, especially the crown problem, once appeared in the production of hot-rolled strip steel in SG Company. The macroscopic characteristic is the thickness difference occurred between the center and edge cross section of hot-rolled plate. Morphological characteristics and forming reasons can be got by analyzing roll wear. Research shows that the main reason for the formation of crown is excessive attrition of work roll in later period, which leading to smaller roll shape. Therefore, shape defects have been effectively controlled after introducing CVC roll contour technology to optimize roll shape. Quality qualified rate of strip shape of hot-rolled strip steel is more than 99.6% percent, and it has been successfully put into application of hot rolling mill.

Hot-rolled strip re-reddening temperature changing law for late ultra fast-cooling in a CSP line

2015 ◽  
Vol 112 (3) ◽  
pp. 305 ◽  
Author(s):  
Lian-yun Jiang ◽  
Guo Yuan ◽  
Jian-hui Shi ◽  
Yue Xue ◽  
Di Wu ◽  
...  
Keyword(s):  
Rolled Strip ◽  
Hot Rolled Strip ◽  
Ultra Fast Cooling ◽  
Fast Cooling ◽  
Hot Rolled

scholarly journals X-SDD: A New Benchmark for Hot Rolled Steel Strip Surface Defects Detection

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 706
Author(s):  
Xinglong Feng ◽  
Xianwen Gao ◽  
Ling Luo
Keyword(s):  
Surface Defect ◽  
Surface Defects ◽  
Steel Strip ◽  
Rolled Strip ◽  
Rolled Steel ◽  
Strip Surface ◽  
Hot Rolled Strip ◽  
Hot Rolled ◽  
Hot Rolled Steel ◽  
Detection Of Defects

It is important to accurately classify the defects in hot rolled steel strip since the detection of defects in hot rolled steel strip is closely related to the quality of the final product. The lack of actual hot-rolled strip defect data sets currently limits further research on the classification of hot-rolled strip defects to some extent. In real production, the convolutional neural network (CNN)-based algorithm has some difficulties, for example, the algorithm is not particularly accurate in classifying some uncommon defects. Therefore, further research is needed on how to apply deep learning to the actual detection of defects on the surface of hot rolled steel strip. In this paper, we proposed a hot rolled steel strip defect dataset called Xsteel surface defect dataset (X-SDD) which contains seven typical types of hot rolled strip defects with a total of 1360 defect images. Compared with the six defect types of the commonly used NEU surface defect database (NEU-CLS), our proposed X-SDD contains more types. Then, we adopt the newly proposed RepVGG algorithm and combine it with the spatial attention (SA) mechanism to verify the effect on the X-SDD. Finally, we apply multiple algorithms to test on our proposed X-SDD to provide the corresponding benchmarks. The test results show that our algorithm achieves an accuracy of 95.10% on the testset, which exceeds other comparable algorithms by a large margin. Meanwhile, our algorithm achieves the best results in Macro-Precision, Macro-Recall and Macro-F1-score metrics.

scholarly journals An improved Vision Transformer-based method for classifying surface defects in hot-rolled strip steel

2021 ◽  
Vol 2082 (1) ◽  
pp. 012016
Author(s):  
Xinglong Feng ◽  
Xianwen Gao ◽  
Ling Luo
Keyword(s):  
Surface Defect ◽  
Surface Defects ◽  
Steel Strip ◽  
Learning Ability ◽  
Rolled Strip ◽  
Strip Surface ◽  
Strip Steel ◽  
Hot Rolled Strip ◽  
Hot Rolled ◽  
Improved Algorithm

Abstract A new Vision Transformer(ViT) model is proposed for the classification of surface defects in hot rolled strip, optimizing the poor learning ability of the original Vision Transformer model on smaller datasets. Firstly, each module of ViT and its characteristics are analyzed; Secondly, inspired by the deep learning model VGGNet, the multilayer fully connected layer in VGGNet is introduced into the ViT model to increase its learning capability; Finally, by performing on the X-SDD hot-rolled steel strip surface defect dataset. The effect of the improved algorithm is verified by comparison experiments on the X-SDD hot-rolled strip steel surface defect dataset. The test results show that the improved algorithm achieves better results than the original model in terms of accuracy, recall, F1 score, etc. Among them, the accuracy of the improved algorithm on the test set is 5.64% higher than ViT-Base and 2.64% higher than ViT-Huge; the accuracy is 4.68% and 1.36% higher than both of them, respectively.

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