Endmill Condition Monitoring and Failure Forecasting Method for Curvilinear Cuts of Nonconstant Radii

Abstract

In this paper, an endmill condition monitoring technique is presented for curvilinear cutting. This algorithm operates without the need for prior knowledge of cutting conditions, tool type, cut curvature, cut direction, or directional rate of change. The goal of this method is an indirect measurement of the tool wear able to indicate when wear is accelerating without direct measurement of the tool. This technique is based on an autoregressive-type monitoring algorithm, which is used to track the tool’s condition using a tri-axial accelerometer. Accelerometer signals are monitored due to the sensor’s relatively low cost and since use of the sensor does not limit the machining envelope. To demonstrate repeatability, eight life tests were conducted. The technique discussed herein successfully delivers prognosis of impending fracture or meltdown due to wear in all cases, providing sufficient time to remove the tools before failure is realized. Furthermore, the algorithm produces similar trends capable of forecasting failure, regardless of tool type and cut geometry. Success is seen in all cases without requiring algorithm modifications or any prior information regarding the tool or cutting conditions.