Simulation and analysis of grinding wheel based on Gaussian mixture model

Yulun CHI , Haolin LI

Front. Mech. Eng. ›› 2012, Vol. 7 ›› Issue (4) : 427 -432.

PDF (459KB)
Front. Mech. Eng. ›› 2012, Vol. 7 ›› Issue (4) : 427 -432. DOI: 10.1007/s11465-012-0350-3
RESEARCH ARTICLE
RESEARCH ARTICLE

Simulation and analysis of grinding wheel based on Gaussian mixture model

Author information +
History +
PDF (459KB)

Abstract

This article presents an application of numerical simulation technique for the generation and analysis of the grinding wheel surface topographies. The ZETA 20 imaging and metrology microscope is employed to measure the surface topographies. The Gaussian mixture model (GMM) is used to transform the measured non-Gaussian field to Gaussian fields, and the simulated topographies are generated. Some numerical examples are used to illustrate the viability of the method. It shows that the simulated grinding wheel topographies are similar with the measured and can be effective used to study the abrasive grains and grinding mechanism.

Keywords

grinding wheel / 3D topographies measurement / Gaussian mixture model / simulation

Cite this article

Download citation ▾
Yulun CHI, Haolin LI. Simulation and analysis of grinding wheel based on Gaussian mixture model. Front. Mech. Eng., 2012, 7(4): 427-432 DOI:10.1007/s11465-012-0350-3

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Hegeman J B J W. Fundamentals of grinding: Surface conditions of ground materials. Dissertation for the Doctoral Degree. Netherlands: University of Groningen, 2000

[2]

Fu Y C, Xu H J, Xu J H. Optimization design of grinding wheel topography for high efficency grinding. Journal of Materials Processing Technology, 2002, 129(1-3): 118-122

[3]

Xie J, Wei F, Zheng J H, Tamaki J, Kubo A. 3D laser investigation on micron-scale grain protrusion topography of truncated diamond grinding wheel for precision grinding performance. International Journal of Machine Tools & Manufacture, 2011, 51(5): 411-419

[4]

Cai R, Rowe W B. Assessment of vitrified CBN wheels for precision grinding. International Journal of Machine Tools & Manufacture, 2004, 44(12,13): 1391-1402

[5]

Nguyen T A, Butler D L. Simulation of precision grinding process,part 1:generation of the grinding wheel surface. International Journal of Machine Tools & Manufacture, 2005, 45(11): 1321-1328

[6]

Xiong G, Feng C, Ji L, Chao F, Liang J. Dynamical Gaussian mixture model for tracking elliptical living objects. Pattern Recognition Letters, 2006, 27(7): 838-842

[7]

Yan L, Rong Y M, Jiang F, Zhou Z X. Three-dimension surface characterization of grinding wheel using white light interferometer. The International Journal of Advanced Manufacturing Technology, 2011, 55(1-4): 133-141

[8]

Huo F W. Measurement and evaluation of the surface topography of fine diamond grinding wheel. Chinese Journal of Mechanical Engineering, 2007, 43(10): 108-113

[9]

Shinozuka M, Deodatis G. Simulation of multi-dimensional Gaussian stochastic fields by spectral representation. Applied Mechanics Reviews, 1996, 49(1): 29-53

[10]

Chakrabarti S, Paul S. Numetical modelling of surface topography in superabrasive grinding. International Journal of Advanced Manufacturing Technology, 2008, 39(1,2): 29-38

[11]

Balasz B, Szatkiewicz T, Krolikowski T. Grinding Wheel Topography Modeling with Application of an Elastic Neural Network. Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. 2007, 4682: 83-90

[12]

Blunt L, Ebdon S. The application of three-dimensional surface measurement techniques to characterizing grinding wheel topography. International Journal of Machine Tools & Manufacture, 1996, 36(11): 1207-1226

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg

AI Summary AI Mindmap
PDF (459KB)

2373

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/