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
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.
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