Abstract

In the past, most researchers have investigated the effect of tool flank wear on the average roughness parameter (Ra) during turning. The Ra parameter, however, is sensitive only to the height variations of the machined workiece profile and is insensitive to the spatial changes to the profile caused by gradual increase in tool wear. In this work, a non-contact vision-based method was used to investigate the effect of tool nose radius wear on the hybrid surface roughness parameters during finish turning. The roughness profile of the workpiece surface diametrically opposite the cutting tool was captured during turning of AISI 1035 steel using a digital camera. A high shutter speed (1/4000 s) was used to freeze the motion of the rotating spindle and obtain a blur-free image of the workpiece. The edge of the workpiece profile was extracted to sub-pixel accuracy using the grey level invariant moment method. The hybrid surface roughness parameters were determined from the workpiece profile. The effect on increased nose wear area on these parameters were investigated. Among these roughness parameters the mean wavelength (Rλa) parameter showed the best correlation with tool nose radius wear with coefficients of determination of 0.9734.

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