The Efficiency Optimization of the Cylindrical Grinding Based on Acoustic Emission Signals

Qi Song

doi:10.4028/www.scientific.net/AMM.494-495.721

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 494-495The Efficiency Optimization of the Cylindrical...

The Efficiency Optimization of the Cylindrical Grinding Based on Acoustic Emission Signals

Abstract:

To improve the efficiency of cylindrical plunge grinding, an optimization of grinding process is developed using the Acoustic emission (AE) signals. The relationship between the grinding feed and grinding depth is established based on the elastic deflection between wheel and workpiece. Acoustic emission (AE) signals are curve fitted through the gauss - Newton method to find the stable point of various grinding processes. Therefore, grinding time of each grinding stage is reduced to improve the grinding efficiency.

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Periodical:

Applied Mechanics and Materials (Volumes 494-495)

Pages:

721-724

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.494-495.721

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Online since:

February 2014

Authors:

Qi Song*

Keywords:

AE Signal, Curve Fitting, Efficiency Optimization, Plunge Grinding

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* - Corresponding Author

References

[1] Li Bo, Guo li. The Surface Roughness of the Acoustic emission based on BP Neural Network Prediction [J]. Journal of Confidential Manufacturing and Automation, 2002, 1: 10 ~ 14.

Google Scholar

[2] Huang Wei, Geng Furong, Wang Yanxue. A New Method of Grinding Force and Surface Roughness Prediction [J]. Aerospace Manufacturing Technology, 2005, 2: 75-78.

Google Scholar

[3] Deng Zhaohui, Cao Defang. The Study of Forecasting System for Grinding Process [J]. Journal of Diamond and Abrasive Mold Process, 2003, 2: 14 ~ 17.

Google Scholar

[4] S. M alkin. Gring Technology and found the and Application of Machining with Abrasives, 93197 1 p.1120.

Google Scholar

[5] XUN, Chen, W. B RIAN one, 'Analysis and Simulation of the Grinding Process, the Tools Manufact. Vol. 36, No. 8, pp.897-906, (1996).

Google Scholar

[6] Hahn, R.S., Vibration Problems and Solution in Grinding, ASTME Paper No. MR 69-246196-9.

Google Scholar