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Single neuron PID based method for deformation suppression during CNC machining of parts

Single neuron PID based method for deformation suppression during CNC machining of parts CNC machining realizes the automatic control of machine tools with digital information, which is an advanced technology widely used in today's machinery manufacturing industry. In the process of NC lathe machining of parts, thin‐walled workpieces are prone to deformation due to poor rigidity and thinner wall thickness. Therefore, it is necessary to study the deformation suppression of NC parts. By combining fuzzy control with single neuron PID and introducing fast non dominated sorting genetic algorithm, the parameters of thin‐walled workpiece milling are optimized. The results show that the neuron PID algorithm of fuzzy control has no overshoot in the environment with or without interference, and has fast response speed and strong anti‐interference ability. In the case verification, the cutting force controlled by fuzzy neuron PID can quickly reach the reference 240 N and remain stable. The removal rate fluctuates less in the range of 8000–12,000. It can improve the metal removal rate while maintaining a constant cutting force, so as to restrain the machining deformation of parts. At the same time, the introduced fast non dominated sorting genetic algorithm can increase the maximum rotational speed to 10,486.5, the maximum feed rate per tooth from 0.075 to 0.112, and the rotational speed is nearly doubled, effectively improving the processing quality, providing a technical reference for the stable control of the NC machining system, and providing a new idea and method for part deformation suppression. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Advanced Control for Applications Wiley

Single neuron PID based method for deformation suppression during CNC machining of parts

Ma, Tinghong; Han, Yajun; Li, Huilan
Advanced Control for Applications , Volume Early View – Feb 24, 2023
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References (19)

Publisher
Wiley
Copyright
© 2023 John Wiley & Sons, Ltd.
eISSN
2578-0727
DOI
10.1002/adc2.122
Publisher site
See Article on Publisher Site

Abstract

CNC machining realizes the automatic control of machine tools with digital information, which is an advanced technology widely used in today's machinery manufacturing industry. In the process of NC lathe machining of parts, thin‐walled workpieces are prone to deformation due to poor rigidity and thinner wall thickness. Therefore, it is necessary to study the deformation suppression of NC parts. By combining fuzzy control with single neuron PID and introducing fast non dominated sorting genetic algorithm, the parameters of thin‐walled workpiece milling are optimized. The results show that the neuron PID algorithm of fuzzy control has no overshoot in the environment with or without interference, and has fast response speed and strong anti‐interference ability. In the case verification, the cutting force controlled by fuzzy neuron PID can quickly reach the reference 240 N and remain stable. The removal rate fluctuates less in the range of 8000–12,000. It can improve the metal removal rate while maintaining a constant cutting force, so as to restrain the machining deformation of parts. At the same time, the introduced fast non dominated sorting genetic algorithm can increase the maximum rotational speed to 10,486.5, the maximum feed rate per tooth from 0.075 to 0.112, and the rotational speed is nearly doubled, effectively improving the processing quality, providing a technical reference for the stable control of the NC machining system, and providing a new idea and method for part deformation suppression.

Journal

Advanced Control for Applications – Wiley

Published: Feb 24, 2023

Keywords: deformation suppression; fast non‐dominated sorting genetic algorithm; fuzzy control; neuron PID; thin‐walled parts

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