SciELO - Scientific Electronic Library Online

Bhattacharyya P., Sengupta D., Mukhopadhyay S., Cutting Force–Based Real–Time Estimation of Tool Wear in Face Milling Using a Combination of Signal Processing Techniques. Mechanical Systems and Signal Processing, 21:2665–2683, 2007. [ Links ]

Franco–Gasca L.A., Romero–Troncoso R. de A., Herrera–Ruiz G., Peniche–Vera R. del R. Reconfigurable Filtering System for Sensorless Signal Acquisition in Machining Processes. International Journal of Advanced Manufacturing Technology, 38:102109, 2008. [ Links ]

Franco–Gasca L.A., Romero–Troncoso R. de A., Herrera–Ruiz G., Peniche–Vera R. del R. FPGA Based Failure Monitoring System for Machining Processes. International Journal of Advanced Manufacturing Technology, 40:676–686, 2009. [ Links ]

Jantunen E. A Summary of Methods Applied to Tool Condition Monitoring in Drilling. International Journal of Machine Tools & Manufacture, 42:997–1010, 2002. [ Links ]

Jemielniak K., Arrazola P.J. Application of AE and Cutting Force Signals in Tool Condition Monitoring in Micro–Milling. CIRP Journal of Manufacturing Science and Technology, 1:97–102, 2008. [ Links ]

Kuljanic E., Totis G., Sortino M. Development of an Intelligent Multisensor Chatter Detection System in Milling. Mechanical Systems and Signal Processing, 23:1704–1718, 2009. [ Links ]

Kurt A. Modelling of the Cutting Tool Stresses in Machining of Inconel 718 Using Artificial Neural Networks. Expert Systems with Applications, 36(6):9645–9657, 2009. [ Links ]

Kuljanic E., Sortino M. A Method Based on Cutting Forces Monitoring Tool Wear in Face Milling. International Journal of Machine Tools & Manufacture, 45:429–34, 2005. [ Links ]

López de Lacalle L.N., Lamikiz A., Sánchez J.A., Fernández de Bustos I. Recording of Real Cutting Forces Along the Milling of Complex Parts. Mechatronics, 16:21–32. 2006. [ Links ]

Mehrabian A., Menha–Mohammad B. A Real–Time Neuro–Adap–tive Controller with Guaranteed Stability. Applied Soft Computing, 8:530–542, 2008. [ Links ]

Patra K., Pal–Surjya K, Bhattacharyya K. Artificial Neural Network Based Prediction of Drill Flank Wear From Motor Current Signals. Applied Soft Computing, 7:929–935, 2007. [ Links ]

Prickett P.W., Johns C. An Overview of Approaches to End Milling Tool Monitoring. International Journal of Machine Tools & Manufacture, 39:105–122, 1999. [ Links ]

Rivero A., Lopez de Lacalle L.N., Penalva M.L. Tool Wear Detection in Dry High–Speed Milling Based Upon the Analysis of Machine Internal Signals. Mechatronics, 18(10):627–633, 2008. [ Links ]

Romero–Troncoso R.J., Herrera–Ruiz G., Terol–Villalobos I., Jáuregui–Correa J.C. Driver current Analysis for Sensorless Tool Breakage Monitoring of CNC Milling Machines. International Journal of Machine Tools & Manufacture, 43:1529–1534, 2003. [ Links ]

Shao H., Wang H.L., Zhao X.M. A Cutting Power Model for Tool Wear Monitoring in Milling. International Journal of Machine Tools & Manufacture, 44:1503–1509, 2004. [ Links ]

Zuperl U., Cus F. Tool Cutting Force Modelling in Ball–End Milling Using Multilevel Perceptron. Journal of Materials Processing Technology, 153–154, 2004. [ Links ]