Intelligent Tool Condition Monitoring System Based on Rough Sets and Mathematical Morphology
The image of cutting tools provides reliable information regarding the extent of tool wear. In this paper, we propose the theory of image processing based on rough sets and mathematical morphology to analyzing the flank faces which are chosen as our monitoring object. First, through plotting the appropriate subset, the rough sets filter is used to enhancement the image of tool wear. Then, the mathematical morphology theory is applied to process the translated binary image. Finally, tool condition monitoring is realized by measuring the area of tool wear. This paper gives the corresponding monitoring principal and proposes a new algorithm to process the cutting tool image. The algorithm is also flexible and fast enough to be implemented in real time for online tool wear or tool condition monitoring.
Kai Cheng, Yingxue Yao and Liang Zhou
L. Zhang et al., "Intelligent Tool Condition Monitoring System Based on Rough Sets and Mathematical Morphology", Applied Mechanics and Materials, Vols. 10-12, pp. 722-726, 2008