Abstract
During high-speed cutting, the tool quality is threatened by a high cutting temperature, and severe wear. Traditionally, these threats are handled by tool replacement, which pushes up the economic cost of production and manufacturing. This paper explores the frictional wear detection of hard alloy tool material during high-speed cutting. Based on the theory of wave motion, the wear process of hard alloy tool material during high-speed cutting was modelled mathematically, and the wear mechanism was analyzed. To reduce the interference of weakly important features, the authors presented a method to analyze the feature importance and an approach to identify the frictional wear of tools, under the high-dimensional small dataset about the monitoring signals of tool material wear. Through experiments, the proposed algorithm was proved feasible in identifying the wear of hard alloy tool material during high-speed cutting. The research provides a theoretical guide for improving the production techniques for cutting of hard alloy material.
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