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IJAT Vol.5 No.3 pp. 420-426
doi: 10.20965/ijat.2011.p0420
(2011)

Paper:

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Grey Prediction of CBN Grinding Process

Neng-Hsin Chiu and Jie-Wei Lee

National Kaohsiung First University of Science and Technology, No2 Jhuoyue Rd., Nanzih, Kaohsiung City, 881, Taiwan, R.O.C

Received:
December 22, 2010
Accepted:
April 7, 2011
Published:
May 5, 2011
Creative Commons License
Keywords:
grinding, monitoring, acoustic emission, grey prediction, wavelet transform
Abstract
Surface grinding is a machining process with unstable quality which is usually deteriorated as the process proceeds. If grinding can be forecast to alarm before unsatisfactory, the process could be controlled better. The purpose of this paper is to construct a grey model for CBN grinding based upon acoustic emission (AE) energy extracted from the AE grinding signal to reflect ground roughness variation. A grey model from the conducted experiment was found to be well correlated with the grinding trends. The prediction accuracy, inor out- of- sample, exceeds 90%, making grey prediction suitable for prognostic monitoring of grinding.
Cite this article as:
N. Chiu and J. Lee, “Grey Prediction of CBN Grinding Process,” Int. J. Automation Technol., Vol.5 No.3, pp. 420-426, 2011.
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