Tool chatter monitoring in turning operations using wavelet analysis of ultrasound waves

This paper presents a new method for tool chatter monitoring using the wavelet analysis of ultrasound waves. Ultrasound waves are pulsed through the cutting tool 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, which are generated as a result of tool chatter, affect 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 multilayer perceptron (MLP) artificial neural network (ANN) was used to correlate the response of the ultrasound sensor to the accelerometer measurement of tool chatter. The main advantage of the ultrasound sensor is its ability to monitor other parameters such as the first contact of the tool and workpiece tool chipping and flank gradual tool wear. Experimental results show that the severity of tool chatter can be successfully monitored using the proposed ultrasound system. The system response to various frequency levels of tool chatter was investigated, however, the measurement of the chatter frequency is beyond the system capability at the current time.