Simulation of Abrasive Belt Topography Based on Generation of Random Rough Surface

Abstract:

In this paper, the real surface topography was measured at first to provide the theoretical bases for developing a novel quick numerical simulation method. The result showed that the protrude height of abrasive belt surface appeared to be non-Gaussian distributed. And its auto-correlation function was found to be in exponential form and anisotropic. By using given skewness, kurtosis and auto-correlation function, the novel simulation method is provided, which is based on Johnson translator system and 2D-linear filter technique. This method overcomes the shortcomings of the experimental method to achieve the required topography of abrasive belt with certain statistic characteristics by using given skewness and kurtosis and auto-correlation function. The comparison between simulated surface and measured topography revealed that they share the same probabilistic characteristics.

• Periodical: Key Engineering Materials (Volume 693)
• Pages: 892-899
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.693.892
• Online since: May 2016
• Authors: Wen Xi Wang, Jian Yong Li, Yue Ming Liu*, Rong Quan Wang, Bo Sun
• Keywords: Abrasive Belt Topography, Johnson Translator System, Random Surface, Simulation

References

[1] M. Nakayama, K. Kudo, T. Hirose, et al. Experimental study of grinding fluids for abrasive-belt grinding of stainless steel, Tribology international. 20 (1987) 133-143.

DOI: 10.1016/0301-679x(87)90043-0

[2] Z. Huang, Y. Huang, W. W. Zhang, et al. The development of cutter location algorithm for the 6-Axis simultaneous CNC abrasive belt grinding complex surface, Key Engineering Materials. 416 (2009) 375-380.

DOI: 10.4028/www.scientific.net/kem.416.375

[3] X. Ren, B. Kuhlenkötter, H. Müller. Simulation and verification of belt grinding with industrial robots, International Journal of Machine Tools and Manufacture. 46 (2006) 708-716.

DOI: 10.1016/j.ijmachtools.2005.07.033

[4] A. Jourani, M. Dursapt, H. Hamdi, et al. Effect of the belt grinding on the surface texture: modeling of the contact and abrasive wear, Wear. 259 (2005) 1137-1143.

DOI: 10.1016/j.wear.2005.02.113

[5] E. J. Salisbury, K. V. Domala, K. S. Moon, et al. A three-dimensional model for the surface texture in surface grinding, part 2: grinding wheel surface texture model, Journal of manufacturing science and engineering. 123 (2001) 582-590.

DOI: 10.1115/1.1391428

[6] X. Zhou, F. Xi. Modeling and predicting surface roughness of the grinding process, International Journal of Machine Tools and Manufacture. 42 (2002) 969-977.

DOI: 10.1016/s0890-6955(02)00011-1

[7] W. P. Dong, P. J. Sullivan, K. J. Stout. Comprehensive study of parameters for characterizing three-dimensional surface topography IV: parameters for characterizing spatial and hybrid properties, Wear. 178 (1994) 45-60.

DOI: 10.1016/0043-1648(94)90128-7

[8] Y. Z. Hu, K. Tonder. Simulation of 3-D random rough surface by 2-D digital filter and Fourier analysis, International Journal of Machine Tools and Manufacture. 32 (1992) 83-90.

DOI: 10.1016/0890-6955(92)90064-n

[9] F. W. HUO, D. M. GUO. Measurement and evaluation of the surface topography of fine diamond grinding wheel, Chinese Journal of Mechanical Engineering. 43 (2007) 108-113.

DOI: 10.3901/jme.2007.10.108

[10] A. Darafon, A. Warkentin, R. Bauer. Characterization of grinding wheel topography using a white chromatic sensor, International Journal of Machine Tools and Manufacture. 70 (2013) 22-31.

DOI: 10.1016/j.ijmachtools.2013.03.003

[11] I. D. Hill, R. Hill, R. L. Holder. Algorithm AS 99: Fitting Johnson curves by moments, Applied Statistics. (1976) 180-189.

DOI: 10.2307/2346692