Assessment of Cutting Tool Condition by Acoustic Emission

Acoustic emission (AE) signals, generated during the machining of steel, were analyzed in order to extract information about the condition of the cutting tool. Drill bits with different cutting edge conditions were used to drill steel specimens while registering the AE generated during cutting. Artificial wear of the drill bits was produced by spark erosion and by mechanical means and was assessed by scanning electron microscopy (SEM). During cutting typical parameters and waveforms of AE and torque were recorded. The relationship between MARSE (Measured Area under the Rectified Signal Envelope) Mean Power (MP) and torque was studied for the different conditions of the drill bits. The evolution of the mobile variance of MP in terms of its moving average was also analyzed with interesting results for determining the condition of the tool. Furthermore, the waveform of AE signals was evaluated through the power spectrum and, from these and from previous results, it was possible to separate the contributions to MP from different AE sources.