TY - GEN
T1 - Endmill condition monitoring and failure forecasting method for curvilinear cuts of non-constant radii
AU - Suprock, Christopher A.
AU - Roth, John T.
AU - Downey, Larry M.
PY - 2007
Y1 - 2007
N2 - 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. 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 sensors 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 prognosis 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.
AB - 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. 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 sensors 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 prognosis 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.
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U2 - 10.1115/MSEC2007-31144
DO - 10.1115/MSEC2007-31144
M3 - Conference contribution
AN - SCOPUS:37349017271
SN - 0791842908
SN - 9780791842904
T3 - Proceedings of the ASME International Manufacturing Science and Engineering Conference 2007, MSEC2007
SP - 507
EP - 516
BT - American Society of Mechanical Engineers
T2 - 2007 ASME International Conference on Manufacturing Science and Engineering
Y2 - 15 January 2007 through 18 October 2007
ER -