Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 62, Issue 6, Pages 3806-3813Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2015.2392713
Keywords
Cutting force; micromilling; online monitoring; probability density; shape singularity; tool wear
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Funding
- National Natural Science Foundation of China [51475443]
- CAS, Chinese Academy of Sciences
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The cutting force variations have long been studied for machining condition monitoring, due to their sensitivity to the tool conditions. These variations could be the statistics of the amplitude, features extracted from frequency components, wavelet coefficients, etc. Different from most current approaches, this paper introduces a novel online approach that directly correlates tool conditions with the force waveform variations and estimates the tool condition based on their corresponding singularity degree density functions. The singularities of waveforms are measured with Holder exponents (HEs), which are extracted from their wavelet transform modulus maxima. Experimental studies have shown that the HEs reflect the changes of tool conditions. The HE features are found robust to working condition variations, and their probability density functions are discriminate for tool state estimation in micromilling.
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