TOOL WEAR PREDICTION FROM ACOUSTIC EMISS
β
P. WILKINSON; R.L. REUBEN; J.D.C. JONES; J.S. BARTON; D.P. HAND; T.A. CAROLAN; S
π
Article
π
1999
π
Elsevier Science
π
English
β 354 KB
We examine the application of an arti"cial neural network to classi"cation of tool wear states in face milling. The input features were derived from measurements of acoustic emission during machining and topography of the machined surfaces. Five input features were applied to the back-propagating ne