scholarly journals Innovative Measurement Of Stress Superposed Steel Strip For Straightening Machines

2021 ◽  
Author(s):  
Fabian Bader ◽  
Lukas Bathelt ◽  
Eugen Djakow ◽  
Werner Homberg ◽  
Christian Henke ◽  
...  
Keyword(s):  
Plastic Deformation ◽  
Strain Hardening ◽  
Surface Defects ◽  
Steel Strip ◽  
High Strength ◽  
Loop Control ◽  
Innovative Strategy ◽  
Control Techniques ◽  
Curvature Measurement ◽  
Roll Type

Higher quality requirements by customers demand higher precision and accuracy from manufacturing processes. Application oriented preparation of semi-finished materials is key for subsequent forming operations, therefore, straightening machines are employed. Straightening strengthens the material by increasing plastic deformation by means of strain hardening, resulting in undesirable reduction in formability when processing high strength materials, in particular. Conventional roll-type straightening machines process either bars or strips. This is achieved upon passing material between rolls arranged in two staggered rows. However, conventional straightening processes do not adapt to the local varying distortion of coiled strips. Innovative, self-correcting process control techniques, which adapt to the initial geometric characteristics of the strip, present a promising approach to fix this issue through optimization of the leveling process. Here, an innovative strategy to improve straightening of high strength steel materials (1.4310) is presented. This implements optimized leveling, adding minimal plastic deformation and, thus, strain hardening. To operate an intelligent straightening machine, a reliable online measurement of the surface defects is fundamentally essential. The MagnaTest, which is developed for material testing, is made feasible for such purposes after calibrating for curvature measurement. Preliminary results are promising in regards to measuring the curvature online, so that the following straightening process can be close loop controlled. The bending measurement is linked to open/closed loop control, therefore providing an optimal straightening result in regards to formability, leveling, and reduced strain hardening.

Research on the Entire Roll Type Shape Meter of Cold Rolling Strip and its Industrial Application

2012 ◽  
Vol 572 ◽  
pp. 359-363 ◽  
Author(s):  
Bing Qiang Yu ◽  
Li Po Yang ◽  
Hong Min Liu
Keyword(s):  
Cold Rolling ◽  
Shape Control ◽  
Steel Strip ◽  
Digital Signal ◽  
Strip Surface ◽  
Loop Control ◽  
Technical Requirements ◽  
Roll Type ◽  
Shape Detecting ◽  
Close Loop Control

In order to increase shape measuring precision of cold strip, based on the shape detecting principle and the digital signal technology, a new entire roll type shape meter is developed thorough theoretical analysis and industrial adjustment to develop the shape detecting roll, the shape signal processing method, the original signal compensation mechanism and so on. The shape meter has good performance and stability, which can effectively avoid the scratch of steel strip surface, accurately detect real online strip shape and provide accurate online shape datum for shape control system. It was applied in 1250 mm cold rolling mill, the actual industrial tests prove that the shape signal was stable and reliable, met the harsh condition and the online technical requirements, and could improve shape quality significantly. And the shape close loop control of the 0.18 mm thin cold strip was successful realized.

Strain Hardening Behaviour of PM Alloys with Heterogeneous Microstructure

2007 ◽  
Vol 534-536 ◽  
pp. 741-744 ◽  
Author(s):  
Giovanni Straffelini
Keyword(s):  
Plastic Deformation ◽  
Strain Hardening ◽  
Flow Behavior ◽  
High Strength Steels ◽  
High Strength ◽  
Acoustic Resonance ◽  
Matrix Microstructure ◽  
The Matrix ◽  
Heterogeneous Matrix ◽  
Localized Plastic Deformation

Tensile stress-strain and dynamic acoustic resonance tests were performed on Fe-C-Ni- Cu-Mo high-strength steels, characterized by a heterogeneous matrix microstructure and the prevalence of open porosity. All materials display the first yielding phenomenon and, successively, a continuous yielding behavior. This flow behavior can be described by the Ludwigson equation and developes through three stages: the onset of localized plastic deformation at the pore edges; the evolution of plastic deformation at the pore necks (where the austenitic Ni-rich phase is predominant); the spreading of plastic deformation in the interior of the matrix. The analytical modeling of the strain hardening behavior made it possible to obtain the boundaries between the different deformation stages.

Effect of diamond burnishing parameters on the state of the processed surface layer of billets made of high-strength "30ХГСН2А-ВД" steel

2020 ◽  
pp. 82-86
Author(s):  
A.N. Shvetsov ◽  
D.L. Skuratov
Keyword(s):  
Surface Layer ◽  
Residual Stresses ◽  
Strain Hardening ◽  
Processing Speed ◽  
Synthetic Diamond ◽  
High Strength ◽  
The State ◽  
Diamond Burnishing

The influence of the burnishing force, tool radius, processing speed and feed on the distribution of circumferential and axial residual strses, microhardness and the depth of strain hardening in the surface layer when pr ssing of "30ХГСН2А-ВД" steel with synthetic diamond "ACB-1" is considered. Empirical dependencies determining these parameters are given. Keywords diamond burnishing, strain hardening depth, circumferential residual stresses, axial residual stresses, microhardness. [email protected], [email protected]

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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