Research on Intelligent Control System of Pressure Forming Equipment for Stator and Rotor

2011 ◽  
Vol 211-212 ◽  
pp. 590-594
Author(s):  
Hong Mei Fan ◽  
Shang Bin Wang ◽  
Yu Sun
Keyword(s):  
Control System ◽  
Intelligent Control ◽  
High Speed ◽  
Product Line ◽  
Intelligent Control System ◽  
Stamping Process

An intelligent control system of pressure forming equipment for stator and rotor is presented. The architecture of the high-speed stamping product line is introduced first. Then the function of the control system is analyzed and the control system is designed. Finally, the stamping process is studied and the intelligent stamping process optimizing system is developed.

Research on Intelligent Control System of High Speed and High Precision Filling Disc Machine

2013 ◽  
Vol 397-400 ◽  
pp. 1164-1168
Author(s):  
Ye Kuan Duan ◽  
Jun Fang Ni
Keyword(s):  
Control System ◽  
Real Time ◽  
High Precision ◽  
Intelligent Control ◽  
High Speed ◽  
Positioning System ◽  
Control Technology ◽  
Intelligent Control System ◽  
Accurate Localization ◽  
Machine Interface

Traditional filling disc assembly requires a lot of manual operations and the efficiency of filling disc is not high. Human-machine interface (HMI) and image positioning system of the filling disc machine are developed in this paper, and the whole system and structure are studied on the programmable control technology. The machine realizes the functions of data real-time collection and fast accurate localization. Equipment has reached the accurate filling disc, and got an excellent application in the enterprises.

Digital twin of the chip formation process

2020 ◽  
pp. 81-86
Author(s):  
Yu.G. Kabaldin ◽  
D.A. Shatagin ◽  
M.S. Anosov ◽  
A.M. Kuz'mishina
Keyword(s):  
Neural Network ◽  
Control System ◽  
Crystal Lattice ◽  
Network Model ◽  
Intelligent Control ◽  
Neural Network Model ◽  
Formation Process ◽  
Chip Formation ◽  
Intelligent Control System ◽  
The Relationship

The formation of chips during the processing of various materials was studied. The relationship between the type of chips, the type of crystal lattice of the material and the number of sliding systems is shown. A neural network model of chip formation is developed, which allows predicting the type of chips. An intelligent control system for the process of chip formation during cutting is proposed. Keywords: chip formation, crystal lattice, neural network model, type of chips. [email protected]

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