Tool wear measurement data from turning of Inconel 718 aircraft engine components were processed by conventional interpolation and neural network based methods, aiming at the on-line prediction of tool wear development. A four-constant empirical model was derived to predict flank wear as a function of cutting time and cutting speed. These results were compared with those obtained from the application of a supervised neural network paradigm for flank wear forecasting.
Empirical and Neural Network Modelling of Tool Wear Development in Ni-Base Alloy Machining / Leone, Claudio; D'Addona, DORIANA MARILENA; Teti, Roberto. - STAMPA. - (2010), pp. 691-698.
Empirical and Neural Network Modelling of Tool Wear Development in Ni-Base Alloy Machining
LEONE, CLAUDIO;D'ADDONA, DORIANA MARILENA;TETI, ROBERTO
2010
Abstract
Tool wear measurement data from turning of Inconel 718 aircraft engine components were processed by conventional interpolation and neural network based methods, aiming at the on-line prediction of tool wear development. A four-constant empirical model was derived to predict flank wear as a function of cutting time and cutting speed. These results were compared with those obtained from the application of a supervised neural network paradigm for flank wear forecasting.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.