A sensorless approach for tool fracture detection in milling by integrating multi-axial servo information

This paper proposes a sensorless approach for realtime tool fracture detection in milling by means of servo information. Cutting force and torque can be estimated in a wide-frequency range by applying disturbance observer to the ballscrew-driven stages and the spindle controllers. By integrating the estimated information in each axis, a fracture-induced variation in cutting force and torque can be accurately captured with parallel sliding Fourier transform which is an analytical approach of low computation load in time–frequency domain. Validation of the proposed method is presented through milling tests of various milling conditions with several fractured endmills.