Abstract
Ultrasound waves are pulsed through the cutting tool insert towards the nose and are reflected back off the cutting edge. Fluctuating states of contact and non-contact between the tool insert and the workpiece, generated as a result of tool chatter, affects the amount of the transmitted ultrasound energy into the workpiece material and, in turn, the amount of the reflected energy. The change in the energy of the echo signals can be related directly to the severity and frequency of tool chatter. Wavelet packet analysis was used to filter the ultrasound signals. A three layer multi-layer perceptron (MLP) artificial neural network (ANN) was used to correlate the response of the ultrasound sensor to the accelerometer measurement of tool tool-workpiece first contact, tool chipping, and flank gradual tool wear.
