Effects of Lubrication in Ferrite Rolling of Interstitial Free Steel

2013 ◽  
Vol 773-774 ◽  
pp. 186-191 ◽  
Author(s):  
Ning Kong ◽  
Kiet Tieu ◽  
Hong Tao Zhu ◽  
Qiang Zhu ◽  
Peter Gandy

Ferrite rolling of interstitial free steel strip in the temperature range 650-850°C can effectively reduce furnace costs and scale formation as a result of lower strip reheating temperatures. Different lubrication conditions of lubricating oil, solid lubricant and dry condition were used during ferrite rolling tests of thin interstitial free steel strip on a 2-high Hille 100 experimental rolling mill. Different rolling speed, rolling temperature and reductions were applied to the rolling process. The rolling force and roll roughness were affected by the lubrication conditions and rolling parameters. Solid lubricant indicated an improved performance in terms of the roll roughness, as well as the oxidation property of the strip surface during ferrite rolling.

Metals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 178
Author(s):  
Ning Kong ◽  
Jie Zhang ◽  
Hongbo Li ◽  
Boyu Wei ◽  
David R. G. Mitchell

A novel polyphosphate lubricant was used and evaluated during hot (ferrite) rolling of an interstitial-free (IF) steel. The texture evolution of these rolled IF steels have been examined by means of X-ray diffraction (XRD) and electron backscatter diffraction (EBSD) measurements. The polyphosphate lubricant shows an improved lubrication performance in terms of the texture optimization compared with lubricating oil and with unlubricated conditions. The γ-fiber texture is enhanced, and less shear texture is produced. This microstructure is responsible for enhanced drawability of ferrite rolled IF steels. The very high thermal stability of the polyphosphate enabled its use at very high temperatures (from 700 to 800 °C). Rolling temperature exerted limited influence on the resulting rolling texture evolution. The polyphosphate lubricant stabilizes the surface texture and reduces the gradient of shear texture through the thickness. The in-grain shear bands are reduced significantly (48.5%) compared with the unlubricated condition. Measured grain orientations indicate that the favorable texture of {111}<112> along the γ-fiber is developed while the undesired α-fiber texture of {001}<110> is effectively suppressed.


2011 ◽  
Vol 337 ◽  
pp. 550-555 ◽  
Author(s):  
Bing Wang ◽  
Jian Lin Sun ◽  
Yuan Yuan Wu

The non-parathion nano organic molybdenum (Nano-Mo) was adopted to substitute for the conventional extreme-pressure and anti-wear additives, uniformly dispersed in water-based cold rolling liquid for steel strips. The tribological properties of the water-based cold rolling liquid were tested by the four-ball machine, and the lubricity of the cold-rolling liquid for steel strip was evaluated on the 4-high cold rolling experiments. Besides, the worn surfaces of the steel balls were observed by an optical microscope. Results indicated that Nano-Mo as additive in water-based cold rolling liquid, compared with the conventional emulsions, PB values was increased by 4%, and friction coefficient and wear scar diameter were decreased by 10.8% and 13.1%, the lubricity of rolling liquid was verified by cold rolling test which showed that this liquid had the excellent lubricant performance to reduce the rolling force, save energy consumption and get thinner strip. Optical microscope was used to observe the strips surface which showed that strip surface streaks were clear, scratches were less and shallow. By roughness test and EDS analysis, defects were filled with nanoparticles, friction and wear were reduced effectively. In addition, tensile properties had been studied after rolling lubrication, but the results showed no significant effect.


Author(s):  
Shao Yimin ◽  
Rao Meng ◽  
Yang Qihui ◽  
Yilin Yuan

As a common defect in the production of high-quality steel strip, chatter marks are easily found on the strip surface which may resulting from inappropriate variation of rolling parameters of a twenty-high rolling mill and the quality of the strip surface can be significantly affected. Therefore, it is critical to understand the underlying relationship between the vibration mechanisms of chatter marks and rolling parameters, furthermore, an appropriate adjustment strategy of rolling parameters is needed to improve the quality of the strip surface. To addressing this problem, a dynamic model of the twenty-high rolling mill, coupling the vertical and horizontal vibrations (because of the variation in friction tension forces), is proposed to investigate the vibration characteristics under different rolling conditions. Based on this dynamic model, effects of rolling force, rolling speed and fluctuations of tension on the vibration of the twenty-high rolling mill are studied. Finally, a rolling parameter adjustment strategy is discussed and presented based on the research results.


Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 706
Author(s):  
Xinglong Feng ◽  
Xianwen Gao ◽  
Ling Luo

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.


2021 ◽  
Vol 227 (2) ◽  
pp. 137-152
Author(s):  
S. K. Chandra ◽  
R. Sarkar ◽  
Sukalpa Choudhury ◽  
Mrinmoy Jana ◽  
P. S. De ◽  
...  

Measurement ◽  
2021 ◽  
pp. 109454
Author(s):  
Xupeng Kou ◽  
Shuaijun Liu ◽  
Kaiqiang Cheng ◽  
Ye Qian
Keyword(s):  

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