Abstract
In this work, an attempt has been made to monitor the tool condition using multiple sensors such as acoustic emission (AE), accelerometer (ACC) and cutting force dynamometer in the microturning of stainless steel with coated tungsten carbide insert upto 60 minutes. Signal processing are carried out in time domain, frequency domain and discrete wavelet transformation (DWT) technique. The AERMS, ACCRMS and the dominant frequencies are found to be uniformly increasing with respect to increase in the tool wear, while Ra, chip width and cutting forces show non-uniform trend. From the frequency domain analysis, it is found that the dominant frequency of the AERMS and ACCRMS signals are between 80-108 kHz and 2.2-4.3 kHz respectively. The result of DWT, indicates that the specific energy of AERMS and ACCRMS of level D4 (62.5-125 kHz) and level D2 (2.5-5 kHz) respectively are found to be dominating among the five levels (D1 - D5) due to the shearing and elastic fracture mechanisms. In the case of force analysis, it is found that the tangential force (Fy) is found to be more sensitive than that of the thrust force (Fx) and feed force (Fz). This study will be useful for the manufacturers, for monitoring the condition of the tool, using the multiple sensors in the microturning of stainless steel 304.