Modeling of the plunge grinding process with self learning systems for monitoring and adaptive control
Article
Mult, HC, Koenig, W, Memis, F et al. (1994). Modeling of the plunge grinding process with self learning systems for monitoring and adaptive control
. 4 981-986.
Mult, HC, Koenig, W, Memis, F et al. (1994). Modeling of the plunge grinding process with self learning systems for monitoring and adaptive control
. 4 981-986.
Plunge grinding operations are considered in this study. The characteristics of two cutting variables (cutting force and the RMS level of Acoustic Emission (AE)) are studied at 52 cutting conditions. Two trainable networks, namely Backpropagation and Abductory Induction Mechanism (AIM) are prepared to predict the cutting variables from the given cutting conditions.
