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.



cited authors

  • Mult, HC; Koenig, W; Memis, F; Tansel, IN

fiu authors

abstract

  • 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.

publication date

  • December 1, 1994

start page

  • 981

end page

  • 986

volume

  • 4