TY - GEN
T1 - DEVELOPMENT OF A CUTTING DIRECTION AND SENSOR ORIENTATION INDEPENDENT MONITORING TECHNIQUE FOR END-MILLING
AU - Roth, John T.
AU - Pandit, Sudhakar M.
N1 - Publisher Copyright:
© 1999 American Society of Mechanical Engineers (ASME). All rights reserved.
PY - 1999
Y1 - 1999
N2 - In the authors' previous work, univariate models were fit to acceleration data to predict impending tool failure. Numerous end-milling life tests, conducted under a wide variety of cutting conditions, demonstrated that the method could consistently warn of impending failure between 6 inches (15 cm) and 8 inches (20 cm) prior to the actual event. This paper presents an improved method that increases the warning time and allows the technique to function independent of the cutting direction or sensor orientation. Using multivariate autoregressive models fit to triaxial accelerometer signals, monitoring indices are developed, verified and the results are compared with those from the univariate models. The multivariate models detected impending failure 30 inches (76 cm) priorto its occurrence, 23.5 inches (60 cm) earlier than with the univariate models. Furthermore, the multivariate models are able to monitor the condition of the tool, regardless of the cutting direction or sensor orientation.
AB - In the authors' previous work, univariate models were fit to acceleration data to predict impending tool failure. Numerous end-milling life tests, conducted under a wide variety of cutting conditions, demonstrated that the method could consistently warn of impending failure between 6 inches (15 cm) and 8 inches (20 cm) prior to the actual event. This paper presents an improved method that increases the warning time and allows the technique to function independent of the cutting direction or sensor orientation. Using multivariate autoregressive models fit to triaxial accelerometer signals, monitoring indices are developed, verified and the results are compared with those from the univariate models. The multivariate models detected impending failure 30 inches (76 cm) priorto its occurrence, 23.5 inches (60 cm) earlier than with the univariate models. Furthermore, the multivariate models are able to monitor the condition of the tool, regardless of the cutting direction or sensor orientation.
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U2 - 10.1115/IMECE1999-0720
DO - 10.1115/IMECE1999-0720
M3 - Conference contribution
AN - SCOPUS:85122763093
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
SP - 597
EP - 603
BT - Manufacturing Science and Engineering
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 1999 International Mechanical Engineering Congress and Exposition, IMECE 1999
Y2 - 14 November 1999 through 19 November 1999
ER -