Abstract
The objective of this article is to propose Wavelet Multi-Resolution Analysis as an effective tool allowing the improvement of the sensitivity of the scalar indicators for the identification of cutting tool’s degradation state during the machining of X200Cr12 steel. Indeed, these indicators are very sensitive to the variations in the temporal signal related directly to the vibrations induced during turning operation. Nevertheless, their reliability is immediately limited in the presence of intense levels of random noise and other machine components. In addition to the Wavelet Multi-Resolution Analysis (WMRA) which brought a solution to this problem, one proposes a new spectral indicator, which one called overall level, to separate the phases characterizing the tool’s wear. The results obtained from this article made it possible to study the phenomena of vibration associated with machining, and to locate the transition point from the normal wear period to the accelerated wear period.
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Babouri, M.K., Ouelaa, N., Djebala, A., Djamaa, M.C., Boucherit, S. (2017). Prediction of Cutting Tool’s Optimal Lifespan Based on the Scalar Indicators and the Wavelet Multi-resolution Analysis. In: Boukharouba, T., Pluvinage, G., Azouaoui, K. (eds) Applied Mechanics, Behavior of Materials, and Engineering Systems. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-41468-3_24
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DOI: https://doi.org/10.1007/978-3-319-41468-3_24
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