Monitoring technology research of tool wear condition based on machine vision

With the improvement of machining automatization, tool condition on-line monitoring has been a crucial problem and paid more attention. The image processing technology is introduced into the condition monitoring of cutting tool wear. The experimental system on the state of cutting tool condition monitor is designed. Through collecting the online images of cutting tool and machined surface, the pulse-couple neutral networks (PCNN) in the bionics is introduced in the monitor of tool wear for the first time in the paper. According to gray intensity in the field of tool wear is higher than the body of the tool and background, using the spatial neighbor and similar cluster gray of pixel, the binary image of the tool wear is segmented, and the field of tool wear is detected. Combined with the connected component integer number is calculated to judge the wear state of cutting tools. This method is proved by experimental results of the image segmentation of tool wear for the different stages in the turning, and the tool wear can be effectively judged.