Grinding is a mechanical removal process applied mainly in finishing operations of hardened workpieces to produce small tolerances with high -quality. Especially, centreless grinding is broadly used in serial production due to the requirement of high accuracy in process. Centreless grinding is used to produce several mechanical components such as, bushings, needles, ball bearings, valves, and stems for shock absorbers. However, the setup of machine tools is very complex and needs long time due to the great number of input variables that should be checked and configured. The acoustic emission monitoring can be used to help the first setup or during the grinding process becoming a on-line detection system. Considering the importance of obtaining an efficient methodology to predict and detect the surface quality and the dimensional errors, a monitoring of the frequency on the spectrum of acoustic emission (EA) was conducted, related to surface roughness Rz, cylindricity, and roundness. The FFT and Wavelet were applied aiming to help the analysis of data and provide the best understanding of the signal and generating an intelligent information in the automation in grinding process. Thus, in this work the results showed that the analysis of the harmonic content of acoustic emission signal is a powerful tool to monitoring the centreless grinding process. (C) 2016 Elsevier Ltd. All rights reserved.
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