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Sensors 2014, 14(11), 21514-21522; doi:10.3390/s141121514

Surface Roughness Evaluation Based on Acoustic Emission Signals in Robot Assisted Polishing

1
Department of Manufacturing Engineering, Industrial Engineering School, National University of Distance Education (UNED), C/Juan del Rosal, 12, E28040-Madrid, Spain
2
Department of Materials and Production Engineering, University of Naples Federico II Piazzale Tecchio, 80, Naples 80125, Italy
*
Author to whom correspondence should be addressed.
Received: 18 July 2014 / Revised: 10 October 2014 / Accepted: 10 November 2014 / Published: 14 November 2014
(This article belongs to the Section Physical Sensors)
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Abstract

The polishing process is the most common technology used in applications where a high level of surface quality is demanded. The automation of polishing processes is especially difficult due to the high level of skill and dexterity that is required. Much of this difficulty arises because of the lack of reliable data on the effect of the polishing parameters on the resulting surface roughness. An experimental study was developed to evaluate the surface roughness obtained during Robot Assisted Polishing processes by the analysis of acoustic emission signals in the frequency domain. The aim is to find out a trend of a feature or features calculated from the acoustic emission signals detected along the process. Such an evaluation was made with the objective of collecting valuable information for the establishment of the end point detection of polishing process. As a main conclusion, it can be affirmed that acoustic emission (AE) signals can be considered useful to monitor the polishing process state. View Full-Text
Keywords: robot assisted polishing; surface roughness; acoustic emission signals; contact force; monitoring robot assisted polishing; surface roughness; acoustic emission signals; contact force; monitoring
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

de Agustina, B.; Marín, M.M.; Teti, R.; Rubio, E.M. Surface Roughness Evaluation Based on Acoustic Emission Signals in Robot Assisted Polishing. Sensors 2014, 14, 21514-21522.

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