Mecheri K., Ouahabi A., Serra R., Rmili W.

Abstract : The mechanical engineering industries have heavily invested in a high speed machine, which requires very careful monitoring of all the machine elements and in particular the cutting tool. There are several approaches to monitoring based on various types of sensors and signal processing techniques. Optimal signal processing analysis is essential to highlighting any anomaly or dysfunction of the cutting tool or of the machining process. The quality of the work-piece is mainly related to the tool’s state. Tool wear is characterized by two principal indicators: VB (flank wear) and KT (crater wear). To ensure good monitoring, it is necessary to correlate the behavior of signals and the evolution of the tool wear. In this perspective, this paper intervenes. Firstly we present a brief bibliographical review on research in this field. Secondly we present some results of the detection of the tool wear by analysis of the signals resulting from various sensors (vibration, acoustic emission, cutting force, current driver). Several signal processing techniques are used and a comparative study is drawn up. Key words: high speed machining, tool wear, signal processing, vibrations, acoustic emission, cutting force, current diver.