Detection of fracture in ceramic cutting tools from workpiece image using sub-pixel edge location

The objective this study is to detect fracture of ceramic cutting tool inserts from the work piece profile signature. The work piece image was captured using a high-resolution digital camera and the surface profile was extracted to sub-pixel accuracy by invariant moment method. The extracted profile was transformed from the spatial domain to frequency domain using Fast Fourier Transform (FFT). Machining experiments were carried out to turn stainless steel using the ceramic cutting tool inserts. The amplitude of the fundamental feed frequency was observed to increase steadily with cutting time during gradual wear. But, significant fluctuations were observed with increase in cutting time when fracture has occurred.