Application of New Techniques of Signal Processing for Detection of Wear Mechanisms in Turning of AISI 4340 Using Acoustic Emission

Abstract

In this study, the short-time Fourier transform (STFT) technique was used to determine the wear mechanisms acting on uncoated and AlCrN-coated carbide tools and their variations during the machining process. To this end, tensile tests were performed on hardened AISI 4340 steel to characterize the acoustic emission (AE) signals and subsequently isolate the steel deformation and fracture mechanisms from the signs of tool wear during the steel turning. Machining tests were carried out using the following parameters: cutting speeds of 150, 200 and 250 m/min and feed rates of 0.10 and 0.20 mm/rev. The results demonstrate that AE signals in conjunction with STFT analysis can be used to identify abrasive wear, adhesive wear and other phenomena that occur during cutting.