Abstract
This paper developed a novel, simple-to-use method for detecting tool failure in cutting. An EEMD filtering and restructuring method is launched according to entropy and correlation of cutting force signal in turning high-strength and high-hardness materials using carbide cutting tools. Then, friction coefficient and mean power theories are adopted to characterize tool failure status using restructured cutting force signal. Finally, an automatic detector is proposed using CUSUM control chart to monitor tool chipping and tool wear failure in real time based on previous analysis and can be verified by semi-finishing experiment. Without any need of other sensor equipment and long computing time, the method can be reliable and simple to operate in detecting tool failure in real time.
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