Machining Tools Wear Condition Detection Based on Wavelet Packet

In order to study the monitor of machining tool condition in machining based on computer vision, the experimental system on the state of machining tool wear is designed. The image processing technology is introduced into the monitor of machining tool wear, a new method of judging the cutting tool state is proposed by extracting the machining surface textual images wavelet packet energy distribution. The images of machined surface are collected, and then preprocessed. The preprocessed images are decomposed by using the wavelet packet, the sub-images contain rich intermediate frequency information are obtained, the characteristics reflecting the machining tool wear condition is extracted by calculating the wavelet packet energy distribution of the images. Experiments shows that there is a strong relativity between the wavelet packet energy distribution of machined surface and machining tool wear state, the tools wear condition can be estimated indirectly, and then the objective of monitoring the tools condition is achieved. It is concluded that the method of judging the machining tool wear condition through extracting the wavelet packet energy distribution of machined surface is simple, and the machining tool wear condition can be judged effectively in this way.