Statistical properties of acoustic emission signals from metal cutting processes

Details Statistical properties of acoustic emission signals from metal cutting processes Statistical properties of acoustic emission signals from metal cutting processes

2004-04-27

arxiv.org/abs/physics/0404128v1

J. Acoust. Soc. Am. 116, 981-986 (2004).

Physics

Data Analysis, Statistics and Probability

16 pages, 7 figures

Scientific paper

10.1121/1.1764831

Acoustic Emission (AE) data from single point turning machining are analysed in this paper in order to gain a greater insight of the signal statistical properties for Tool Condition Monitoring (TCM) applications. A statistical analysis of the time series data amplitude and root mean square (RMS) value at various tool wear levels are performed, �nding that ageing features can be revealed in all cases from the observed experimental histograms. In particular, AE data amplitudes are shown to be distributed with a power-law behaviour above a cross-over value. An analytic model for the RMS values probability density function (pdf) is obtained resorting to the Jaynes' maximum entropy principle (MEp); novel technique of constraining the modelling function under few fractional moments, instead of a greater amount of ordinary moments, leads to well-tailored functions for experimental histograms.

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