Application of wavelet packet analysis in drill wear monitoring

In this work, an attempt has been made to develop a drill wear monitoring system which is independent to cutting conditions of the drilling process. A cost effective Hall-effect current sensor, which does not interfere with the process, has been used for acquiring motor current signature during drilling under different cutting conditions. An advanced signal processing technique, the wavelet Packet transform has been used on the acquired current signature to extract features for indirect representation to the amount of drill wear. Experimental sensitivity analysis reveals that in comparison to time domain features, wavelet Packet features are more sensitive to flank wear and less sensitive to the cutting conditions. A multilayer neural network model has then been developed to correlate the extracted wavelet Packet features with drill flank wear. Experimental results show that the proposed drill wear monitoring system can successfully predict the flank wear with acceptable accuracy.