Method of monitoring wearing and breakage states of cutting tools based on Mahalanobis distance features

The Mahalanobis distance features proposed by Mahalanobis, an Indian statistician, can be used in an automatic online cutting tool condition monitoring process based on digital image processing. In this paper, a new method of obtaining Mahalanobis distance features from a tool image is proposed. It can automatically divide the component groups for calculating the Mahalanobis distance based on the gray level of wearing or breakage regions in a tool image. The wearing region can be divided into a high gray level component group and the tool-blade into low one. The relation between the Mahalanobis distance features of component groups and tool conditions is investigated. The results indicate that the Mahalanobis distance features of the high gray level component group are related with the wearing state of the tool and the low gray level component group correlated with the breakage of tool. The results also indicate that the Mahalanobis distance features have a higher sensitivity in expressing wearing or breakage states of tools.