scholarly journals Positioning Accuracy of CNC Machine Tools. Thermal Effect Prediction Using Neural Network.

1996 ◽  
Vol 62 (599) ◽  
pp. 2686-2691 ◽  
Author(s):  
Liang CHEN ◽  
Yasuhiro HIROTA ◽  
Masaomi TSUTSUMI ◽  
Nobuhiko NISHIWAKI
Keyword(s):  
Neural Network ◽  
Thermal Effect ◽  
Machine Tools ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Positioning Accuracy

The Effects of Tuning Controller Gains for Servo Feed Unit Positioning Accuracy

2011 ◽  
Vol 317-319 ◽  
pp. 1974-1978
Author(s):  
Ling Lin Kong ◽  
Duan Neng Li ◽  
Ke Li
Keyword(s):  
Machine Tools ◽  
Laser Interferometer ◽  
Servo System ◽  
Pi Controller ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Positioning Accuracy ◽  
Ac Servo ◽  
And Control ◽  
Feed Unit

Positioning accuracy of servo feed unit makes an important effect to processing precision in CNC machine tools. The effects in positioning accuracy mainly are the precisions of mechanism and servo system. And the actions of tuning controller gains should directly affect the servo system precision. This paper, a servo system model and its P/PI controller has been formulated and simulated, using an AC servo feed unit as a tested. Through tuning gains of P/PI controller, analyses and control the effects for the feed unit positioning accuracy. Ultimately, experiments have been carried out to test feed unit by laser interferometer. Its shows that tuning gains of P/PI controller, which given in paper, has effectively improved the positioning accuracy of servo feed unit.

Research of On-Line Monitoring Technology of Machining Accuracy of CNC Machine Tools

2013 ◽  
Vol 846-847 ◽  
pp. 268-273
Author(s):  
Rong Bo Shi ◽  
Zhi Ping Guo ◽  
Zhi Yong Song
Keyword(s):  
Neural Network ◽  
Machine Tools ◽  
Cnc Machine Tools ◽  
Frequency Domain Method ◽  
Machining Accuracy ◽  
Cnc Machine ◽  
Monitoring Technology ◽  
The Neural Network ◽  
Network Identification ◽  
On Line

This paper analyzes CNC machine tools machining error sources, put forward a kind of on-line monitoring technology of CNC machine tools machining accuracy based on online neural network. Through the establishment of CNC machine tools condition monitoring platform, collection sensor signal of the key components of CNC machine tools, using time domain and frequency domain method of the original signal processing, extract the characteristic related to machining accuracy change, input to the neural network, identification the changes of machining accuracy. The experimental results show that, the on-line monitoring technology based on neural network, can identify the changes of machining accuracy.

Intelligent Machine Tool – A Thermal Diagnostic System for a CNC Pretensioned Ball Screw

2015 ◽  
Vol 220-221 ◽  
pp. 491-496
Author(s):  
Mirosław Pajor ◽  
Jacek Zapłata
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Machine Tools ◽  
Thermal Deformation ◽  
Ball Screw ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Positioning Accuracy ◽  
Machine Control ◽  
The Impact

The paper presents a compensation system of thermal deformation for conventional feed axes applied in CNC machine tools allowing for an effective reduction in the impact of heat generated during its operation on the positioning accuracy of the axis. The result has been achieved by equipping feed screws with thermistor temperature sensors. Wiring sensors was led out through an axial bore in the screw and through a rotating electrical connector to an acquisition device coupled with the control system of the CNC machine. An algorithm based on neural networks was implemented in the machine control system, which allows for the online calculation and compensation of heat deformation of feed screws. The algorithm takes into account a variation of thermal deformation values as a function of the table position and the current distribution of the temperature field of the screw and machine. The paper presents a user-friendly method for implementing algorithms containing neural networks in the machine control system. The proposed compensation method has been verified by measuring the linear accuracy of the feed axis positioning. The obtained results confirm the effectiveness of the proposed method in reducing the impact of thermal deformation errors on the positioning accuracy of the axis in CNC machine tools.

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