Author/Authors :
Salimi Beni، A. نويسنده , , Zadshakoyan، M. نويسنده Department of Manufacturing Engineering, Faculty of Mechanical Engineering, University of Tabriz, Tabriz, Iran. , , Ozdemir، A. نويسنده Mechanical Education Department, Faculty of Technical Education, University of Gazi, Ankara, Turkey. , , Seidi، E. نويسنده Department of Agricultural Engineering, Faculty of Agriculture, University of Payame Noor. Tehran, Iran. ,
Abstract :
In automation flexible manufacturing systems, tool wear detection during the cutting process is one of the
most important considerations. This study presents an intelligent system for online tool condition monitoring in drilling
process .In this paper, analytical and empirical models have been used to predict the thrust and cutting forces on the
lip and chisel edges of a new drill. Also an empirical model is used to estimate tool wear rate and force values on the
edges of the worn drill. By using of the block diagram of machine tool drives, the changes in the feed and spindle motor
currents are simulated, as wear rate increases. To predict tool wear rate in drill, Fuzzy logic capabilities have been
used to develop intelligent system. The simulated results presented in MATLAB software show the effectiveness of the
proposed system for on-line drill wear monitoring.
