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Online PCBN tool failure monitoring system based on acoustic emission signatures

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4 Author(s)
Liao, T.W. ; Dept. of Ind. & Manuf. Syst. Eng., Louisiana State Univ., Baton Rouge, LA, USA ; Zou, Q. ; Mann, L. ; Zodhi, M.E.

The paper describes an online tool failure monitoring system based on acoustic emission (AE) signatures. The system was developed primarily to detect failure of polycrystalline cubic boron nitride (PCBN) inserts in milling high-chromium materials. In face milling of high-chromium materials, almost without exception, PCBN inserts fail due to fracture on the nose or rake face. The change in the root mean square of AE signals (AE ΔRMS) was found to be the best indicator of the tool failure process for the subject tool-work combination. From the experiments, the critical values of AE ΔRMS where the tool fractures, called AE ΔRMSc, were obtained. Regression analysis was performed to fit a model of |ΔRMSc| as a function of feed rate and depth of cut. The regression model was then used to estimate the values of |ΔRMSc| for conditions that were excluded from the experiment. The accuracy of the monitoring system was tested with simulated as well as actual experiments

Published in:

Science, Measurement and Technology, IEE Proceedings -  (Volume:142 ,  Issue: 5 )

Date of Publication:

Sep 1995

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