RESEARCH ARTICLE

Simulation and analysis of grinding wheel based on Gaussian mixture model

  • Yulun CHI ,
  • Haolin LI
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  • Mechanical Engineering College, University of Shanghai for Science and Technology, Shanghai 200093, China

Received date: 08 Oct 2012

Accepted date: 17 Oct 2012

Published date: 05 Dec 2012

Copyright

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg

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.

Cite this article

Yulun CHI , Haolin LI . Simulation and analysis of grinding wheel based on Gaussian mixture model[J]. Frontiers of Mechanical Engineering, 2012 , 7(4) : 427 -432 . DOI: 10.1007/s11465-012-0350-3

Acknowledgements

This work was financially supported by National Science and Technology Key Project (2011ZX04003-022) and Shanghai Science Technology Commission (10DZ2292100).
Appendix
This set includes four 3D height parameters [9]:
SqThe RMS value of the departures within the sampling area
SzThe absolute height of the five highest peaks and the depths of the deepest valleys within the sampling area
SskAsymmetry of surface deviations about the mean plane
SkuPeakness or sharpness of the surface height distribution
This set includes four 3D spatial parameters [9]:
SdsNumber of summits of a unit sampling area
StrLong crestness or uniform texture aspect
StdPronounced direction of the surface texture
SalShortest autocorrelation length that the areal autocorrelation function decays to 0.2
This set includes three 3D hybrid parameters [9]:
SΔqRMS value of the surface slope within the sampling area
SscAverage of the principle curvatures of the summits within the sampling area
SdrRatio of the increment of the interfacial area of a surface over the sampling area
This set includes six 3D functional parameters [9]:
SbiRatio of the RMS deviation over the surface height at 5% bearing area
SciRatio of the void volume of the unit sampling area at the core zone over the RMS deviation
SviRatio of the void volume of the unit sampling area at the valley zone over the RMS deviation
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