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Advanced signal processing in acoustic emission monitoring systems for machining technology

This work is focused on the application of acoustic emission (AE) based monitoring systems to machining processes. It describes the most common advanced signal processing methods used in this type of systems such as continuous and discrete transforms (Fourier, Gabor and Wavelet) and statistical analysis methods (amplitude distribution method and the entropic distance method). Besides, some of the most relevant papers illustrating the mentioned signal processing methods have been discussed. The principal machining technology aspects considered for AE based sensor catastrophic tool failure and chip formation.

by: E.M. Rubio(1), R. Teti(2), I.L. Baciu(2)
(1)Dept. of Manufacturing Engineering, University of Spain (UNED), Juan del Rosal,12, Madrid, Spain
(2)Dept. of Materials &Production Engineering, University of Naples Federico II, P.le Tecchio 80, Naples, Italy

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IPROMS_AE.pps304.5 KB
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Submitted by Baciu on Mon, 03/07/2006 - 1:23pm.
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Suitable choice
Submitted by charles on Tue, 04/07/2006 - 10:27pm.

Hello authors,

A good summary of acoustic emission based monitoring systems to machining processes. Out of all these methods which one could be more suitable for fast monitoring with adequate accuracy?

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Suitable choice
Submitted by Eva Rubio on Wed, 05/07/2006 - 5:13pm.

First of all, thank you for your interest in the work.

Then, about your question, say that: it is not possible to select a unique method as the best for a fast monitoring and a determined level of accuracy because it depends on the concrete case under analysis.

In general, it is possible to affirm that:

The implementation of the Continuous Transforms is expensive from the point of numeric and computational view but they usually reach s very good level of accuracy since they collect all the information about the signal.

The Discrete Transforms and the Statistical methods can provide a quite adequate level of accuracy using a smaller numeric and computational effort. They can be considered quicker, with regard to the previous methods showed.

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