An experimental investigation on monitoring of crater wear in turning using ultrasonic technique

Tool life prediction and tool change strategies are now based on most conservative estimates of tool life from past tool wear data. Hence usually tools are underutilized. In an unmanned factory, this has the effect of increased frequency of the tool changes and therefore increased cost. An ultrasound online monitoring of crater wear of the uncoated carbide insert during the turning operation is presented. The method relies on inducing ultrasound waves in the tool, which are reflected by side flank surface. The amount of reflected energy is correlated with crater wear depth. Various ultrasonic parameters are considered for defining the crater wear and individual contribution of each parameter is analyzed. The ultrasonic parameters, amplitude, pulse width and root mean square (RMS) of the signal are used to quantify the crater depth and width. The power spectrum analysis of received signals shows the importance of frequency components in defining the tool wear. In the presented work, the normalizing of signals are carried out by insert hole, which is provided for clamping. This signal is not influenced by the wear but affected by other factors like tool material variation, improper couplant, temperature, etc. The response of the wear signal is normalized to the response of hole signal by mathematical division. A new approach adaptive neuro-fuzzy inference system (ANFIS) for monitoring of crater in carbide insert is presented. This improves the system accuracy and eliminates the limitation in statistical modeling that was presented in previous studies.