Traditionally, tool wear monitoring systems are based on the signals of cutting force, cutting temperature, cutting power, acoustic emission, vibration, etc. Those signals are all sensitive to tool wear, but they can not give the exact amount of tool wear. The monitoring strategies are generally designed qualitatively rather than quantitatively. This study reports a quantitative strategy for tool wear monitoring based on a displacement sensor which can estimate the real- Time tool tip receding. The relationship between tool wear and tool tip receding is modelled. A real time quantitative tool wear estimation strategy is suggested and verified with experiments. © Springer-Verlag Berlin Heidelberg 2010.
CITATION STYLE
Shi, X. H., Shao, H., & Li, J. (2010). A quantitative strategy for tool wear monitoring in turning. In Advances in Intelligent and Soft Computing (Vol. 66 AISC, pp. 647–656). Springer Verlag. https://doi.org/10.1007/978-3-642-10430-5_50
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