Application of convolutional neural networks for prediction of strip flatness in tandem cold rolling process

2021 ◽  
Vol 68 ◽  
pp. 512-522
Author(s):  
Yu Wang ◽  
Changsheng Li ◽  
Lianggui Peng ◽  
Ruida An ◽  
Xin Jin
Keyword(s):  
Neural Networks ◽  
Cold Rolling ◽  
Convolutional Neural Networks ◽  
Rolling Process ◽  
Strip Flatness ◽  
Tandem Cold Rolling

scholarly journals Investigation and Optimization of Load Distribution for Tandem Cold Steel Strip Rolling Process

Metals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 677 ◽  
Author(s):  
Xin Jin ◽  
Changsheng Li ◽  
Yu Wang ◽  
Xiaogang Li ◽  
Yongguang Xiang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Cold Rolling ◽  
Prediction Model ◽  
Load Distribution ◽  
Rolling Mill ◽  
Fitness Function ◽  
Steel Strip ◽  
Rolling Process ◽  
Cold Rolling Mill ◽  
Tandem Cold Rolling

In order to improve the cold rolled steel strip flatness, the load distribution of the tandem cold rolling process is subject to investigation and optimization. The strip deformation resistance model is corrected by an artificial neural network that is trained with the actual measured data of 4500 strip coils. Based on the model, a flatness prediction model of strip steel is established in a five-stand tandem cold rolling mill, and the precision of the flatness prediction model is verified by rolling experiment data. To analyze the effect of load distribution on flatness, the flatness of stand 4 is calculated to be 7.4 IU, 10.6 IU, and 16.8 IU under three typical load distribution modes. A genetic algorithm based on the excellent flatness is proposed to optimize the load distribution further. In the genetic algorithm, the classification of flatness of stand 4 calculated by the developed flatness prediction model is taken as the fitness function, with the optimal reduction of 28.6%, 34.6%, 27.3%, and 18.6% proposed for stands 1, 2, 3, and 4, respectively. The optimal solution is applied to a 1740 mm tandem cold rolling mill, which reduce the flatness classification from 10.8 IU to 3.2 IU for a 1-mm thick steel strip.

scholarly journals An Advanced 3D Mathematical Model for a 6-high Tandem Cold Rolling Process

2017 ◽  
Vol 207 ◽  
pp. 1379-1384 ◽  
Author(s):  
Xiawei Feng ◽  
Pierre Montmitonnet ◽  
Quan Yang ◽  
Anrui He ◽  
Xiaochen Wang
Keyword(s):  
Mathematical Model ◽  
Cold Rolling ◽  
Rolling Process ◽  
Tandem Cold Rolling
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