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Proceedings Paper

Recognition of chatter type based on improved neural network
Author(s): Xiaozheng Xie; Yongpeng Xie; Rongzhen Zhao; Wuyin Jin; Yunping Yao
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Paper Abstract

By studying chatter dynamic model, this paper discusses chatter phenomenon between metal cutting tool and workpiece during the cutting. From the point of energy, phase position difference of chatter mark, phase position difference of vibration mode, lagging phase position angle and change rate about cutting force relative to the cutting speed are respectively determined as characteristic parameter of regenerative, coupling vibration, lagging and fricative mode of chatter. With the four input parameters, multilayer feed forward neural network learning algorithm is used to diagnose the type of cutting chatter, and experiments show that this method is effective.It is essential to take appropriate measures on vibration suppression.

Paper Details

Date Published: 14 March 2013
PDF: 7 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87682K (14 March 2013); doi: 10.1117/12.2010889
Show Author Affiliations
Xiaozheng Xie, Lanzhou Univ. of Technology (China)
Yongpeng Xie, Lanzhou Petrochemical Company Sewage Treatment Plant (China)
Rongzhen Zhao, Lanzhou Univ. of Technology (China)
Wuyin Jin, Lanzhou Univ. of Technology (China)
Yunping Yao, Lanzhou Univ. of Technology (China)


Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)

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