scholarly journals Coiling Temperature Control Using Temperature Measurement Method for the Hot Rolled Strip in the Water Cooling Banks

2010 ◽  
Vol 46 (8) ◽  
pp. 463-471 ◽  
Author(s):  
Shigemasa NAKAGAWA ◽  
Hisayoshi TACHIBANA ◽  
Tatsuro HONDA ◽  
Chihiro UEMATSU
Keyword(s):  
Temperature Measurement ◽  
Temperature Control ◽  
Measurement Method ◽  
Rolled Strip ◽  
Water Cooling ◽  
Coiling Temperature ◽  
Hot Rolled Strip ◽  
Hot Rolled ◽  
Coiling Temperature Control

Prediction of Coiling Temperature of Hot Rolled Strip Based on BP Neural Network

2014 ◽  
Vol 633-634 ◽  
pp. 679-683
Author(s):  
En Yang Liu ◽  
Wen Peng ◽  
Ning Cao ◽  
Si Rong Yu ◽  
Jun Xu ◽  
...  
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Rolled Strip ◽  
Laminar Cooling ◽  
Coiling Temperature ◽  
Online Application ◽  
Hot Rolled Strip ◽  
Highly Nonlinear ◽  
Rolling Plant ◽  
Hot Rolled

Coiling temperature of hot rolled strip is one of the important parameters which affect performances of hot rolled strip. The control of coiling temperature is highly nonlinear and time-varying. Based on the laminar cooling control system of a hot rolling plant, a coiling temperature prediction model based on BP neural network was established. Many factors which affect coiling temperature control were taken into account, and the BP neural network was trained by actual production data. The simulation was carried out, which indicates that coiling temperature can be predicted precisely, and the BP neural network model has the prospect of online application.

scholarly journals Production of Directly Quenched High-Strength Hot-Rolled Strip Steels - Influence of Rolling and Cooling Conditions on Mechanical Properties and Flatness

2016 ◽  
Vol 854 ◽  
pp. 29-34
Author(s):  
Joachim Schöttler ◽  
Thorsten Maiwald ◽  
Gunnar Linke
Keyword(s):  
Mechanical Properties ◽  
High Strength ◽  
Cost Effective ◽  
Rolled Strip ◽  
Coiling Temperature ◽  
Hot Rolled Strip ◽  
Direct Quenching ◽  
Cooling Conditions ◽  
Plant Trials ◽  
Hot Rolled

The production of hot-rolled sheets of high-strength and wear-resistant special structural steels by direct quenching from the rolling heat is a cost effective and energy-saving alternative to traditional production via downstream quenching the previously cut-to-length plates. Reaching the required strength and toughness parameters in combination with best flatness of the sheets requires strict compliance with the pre-set rolling and cooling conditions over the entire strip width. Using two high-strength low-alloyed steels, plant trials have been carried out to study the effect of the cooling conditions and the coiling temperature on mechanical properties, impact toughness and flatness of cut-to-length sheets made of hot-rolled strip. The results showed that by applying optimized cooling pattern and low coiling temperatures, high-strength steel sheets with outstanding mechanical properties and good flatness can be produced.

scholarly journals Effect of Coiling Temperature on Oxide Scale of Hot-Rolled Strip

2011 ◽  
Vol 415-417 ◽  
pp. 853-858 ◽  
Author(s):  
Xiang Long Yu ◽  
Zheng Yi Jiang ◽  
Xiao Dong Wang ◽  
Dong Bin Wei ◽  
Quan Yang
Keyword(s):  
Phase Composition ◽  
Oxide Scale ◽  
Low Carbon Steel ◽  
Rolled Strip ◽  
Low Carbon ◽  
Hot Strip Rolling ◽  
Coiling Temperature ◽  
Strip Rolling ◽  
Hot Rolled Strip ◽  
Hot Rolled

The influence of the coiling temperature, ranging from 550 to 570°C, on the morphology and the phase composition of the oxide scale formed on the microalloyed low carbon steel for automobiles after hot strip rolling was investigated. Physicochemical characteristics of the oxide scales were examined and their formation mechanism was discussed. Thickness of the oxide scale is in the range of 8-11µm and decreases with a decrease of coiling temperature. The microstructure and phase composition, XRD analysis shows a large amount of magnetite (Fe3O4) and some sparse hematite (Fe2O3) exist on the surface of hot rolled strip when the coiling temperature reduces from 570 to 550°C. The coiling temperature substantially affects the internal microstructure and magnetite phase.

Study on CCD laser scanning flatness measurement method for hot rolled strip

2015 ◽  
Vol 42 (8) ◽  
pp. 600-607 ◽  
Author(s):  
L. Zhao ◽  
Q. Ouyang ◽  
D. Chen ◽  
X. Zhang ◽  
Y. Zhang
Keyword(s):  
Measurement Method ◽  
Laser Scanning ◽  
Rolled Strip ◽  
Hot Rolled Strip ◽  
Hot Rolled ◽  
Flatness Measurement

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.

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