rolling mill
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2022 ◽  
Vol 1049 ◽  
pp. 96-101
Author(s):  
Quang Nguyen ◽  
Alexander Sergeevich Aleshchenko

The present article discusses the cylindrical mandrel wear change during rolling using MISIS - 130 D mill depending on the type of rolled billets materials used. The research on the mandrel wear of the screw rolling mill during pipes elongation was carried out using the finite element method (FEM). The results of the wear modeling showed that the depth of the metal removed on the mandrel surface during stainless steel pipes elongation was higher as compared to alloyed and carbon steel pipes. The significant wear of the mandrel during stainless steel pipe rolling can be explained by the rise in the applied metal force resulting from the introduction of alloying components such as chromium and nickel into rolled billets materials. Consequently, the obtained modeling results can allow predicting the service life of working tools.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jiang Ji ◽  
Chen Zhao ◽  
Yongqin Wang ◽  
Tuanmin Zhao ◽  
Xinyou Zhang

To solve the problems of difficult fault signal recognition and poor diagnosis effect of different damage in the same position in rolling mill bearing at low speed, a fault diagnosis method of rolling mill bearing based on integration of EEMD and DBN was proposed. The vibration signals in horizontal, axial, and vertical directions were decomposed and reconstructed by EEMD, and frequency domain analysis was carried out by using refined spectrum. Then, the signal's time-frequency domain index, rolling force, and torque component feature vector were input into genetic algorithm (GA) to optimize DBN model classification. In order to verify the effectiveness of the method, the experimental study was carried out on the two-high experimental rolling mill. The results show that EEMD combined with thinning spectrum can solve the problem of fault feature extraction well. Compared with time-frequency domain characteristic input, the prediction accuracy of DBN model is obviously improved. And the accuracy of GA-DBN model is higher, and the accuracy is 98.3%, and the time taken to diagnose is significantly reduced. Finally, the fault classification of different parts of bearings and the fault diagnosis of different damage in the same part are realized, which provides a good theoretical basis for the fault diagnosis of low-speed bearings and has important engineering significance.


2021 ◽  
Vol 7 (4) ◽  
pp. 125-129
Author(s):  
Roman Ďurčík ◽  
Ladislav Morovič ◽  
Michal Kán ◽  
Milan Mojžiš

The paper deals with the issue of eccentricity in the technological node of the piercing press, under selected conditions, which result from the possibilities of production in the conditions of ŽP a.s. These conditions were verified and adapted to the rolling process. This process consisting of individual technological nodes on the rolling mill, in which eccentricity is created on the piercing press and the following steps eliminate it in other technological nodes. For quality analysis of manufacturing tubes using numerical simulation, it is necessary to know the actual state of eccentricity creation on the rolling mill. A numerical simulation of piercing under different input conditions was used (software DEFORM-3D) and was performed for several different charge states before entering onto the piercing press. The eccentricity itself has a significant effect on the resulting geometric quality of the tubes.


2021 ◽  
pp. 26-31
Author(s):  
S. M. Bratan ◽  
S. I. Roshchupkin ◽  
A. O. Kharchenko ◽  
S. V. Belousov

2021 ◽  
Author(s):  
Magna Paulina de Souza Ferreira ◽  
Márcio da Silva Arantes ◽  
Jesimar da Silva Arantes ◽  
Renan Bonnard ◽  
Claudio Fabiano Motta Toledo

Abstract A scientific challenge on industrial production is to mathematically represent a production process, and this challenge increases when describing production processes with stochastic behavior. The present paper will be approaching a specific part of the production process of soybean oil, where the main objective is to maximize the oil extraction by keeping the thicknesses of the soybean flakes within an operating range. We propose a method, based on a mathematical stochastic model, to obtain pressure setpoints that produce flakes as ideal as possible for oil extraction. The results reported are achieved by applying the proposed method in the industry with improvements within the process in terms of time and quality.


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