A New Approach to Automatic Detection of Life of Coated Tool Based on Acoustic Emission Measurement

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Abstract
Characteristic features of acoustic emission (AE) signals are analyzed and measured during turning of medium carbon steel with both coated and uncoated tools. It was found that the AE signal changes from burst-type to continuous-type as the coated tool is worn away and the ceramic coating is removed. The AE signal further changes to one with a large amplitude and variation as the tool approaches termination. A procedure is proposed to classify the AE signal into three categories based on the experimental results and to identify the condition of tool by AE signal measured employing the pattern recognition technique. Further cutting experiments proved that the state of wear and the life of the coated tool can be identified by the method proposed.

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