A Study of a New ELID Grinding Fluid by BP Neural Network Model

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Electronic in-process dressing (ELID) grinding will be a main technology of ultra-precision grinding which has been widely adopted to the ultra-precision and high effectively machining of hard and brittle materials. This study puts forward a new environmental friendly bamboo charcoal bonded (BCB) grinding wheel and develops a new ELID grinding fluid. An oxide layer is mostly determined by the electric performance of grinding fluid in the experiment. This paper founds a model to forecast grinding fluid’s electric performance by BP neural network and MATLAB. This method can be used in developing of ELID grinding machining fluid to improve the ELID grinding effect.

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1792-1796

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June 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] Itoh Nobuhide, Ohmori Hitoshi. Development of metal free conductive bonded diamond wheel for environmentally-friendly electrolytic In-process Dressing (ELID) grinding[J]. New diamond and Frontier carbon technology, V14, n4, 2004, pp.224-238.

DOI: 10.1299/jsmelem.2005.1.225

Google Scholar

[2] Akihiko Nemoto, Nobuhide Itoh, Teruko Katoh, etc. Development of R.B. ceramics bonded diamond wheel for eco-friendly ELID grinding[J]. Superhard Material Engineering, 2005 (4): 40-46.

DOI: 10.1299/jsmelem.2005.1.225

Google Scholar

[3] Zhejun Yuan, Dongming guo, Jialiang guan. ELID Mirror Grinding Technology [J]. Manufacturing Technology & Machine Tool, 2001(2): 38-40.

Google Scholar

[4] Zhexue Ge, Zhiqiang Sun. Neural Network Theory and MATLAB R2007 implementation [M]. Electronics Industry University Press, (2007).

Google Scholar

[5] Ausanio G, Barone AC, Iannotti V, Lanotte L, Amoruso S, Bruzzese R, Vitiello M, ppl. Phys. Lett, (2004).

DOI: 10.1063/1.1815065

Google Scholar

[6] Fogel L J, WalshM J. Artificial Intelligence through Simulated Evolution [M]. Chichester: John Wiley2003.

Google Scholar

[7] Fredric M. Ham. Principles of Neurocomputing for Science & Engineering [M]. Beijing: China Machine Press, (2003).

Google Scholar