Persona: Agustina Tejerizo, Beatriz De
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0000-0003-0149-6928
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Agustina Tejerizo
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Beatriz De
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Publicación Analysis of Force Signals for the Estimation of Surface Roughness during Robot-Assisted Polishing(MDPI, 2018-08-15) Agustina Tejerizo, Beatriz De; Marín Martín, Marta María; Teti, Roberto; Rubio Alvir, Eva María; MDPIIn this study feature extraction of force signals detected during robot-assisted polishing processes was carried out to estimate the surface roughness during the process. The purpose was to collect significant features from the signal that allow the determination of the end point of the polishing process based on surface roughness. For this objective, dry polishing turning tests were performed on a Robot-Assisted Polishing (RAP) machine (STRECON NanoRAP 200) during three polishing sessions, using the same polishing conditions. Along the tests, force signals were acquired and offline surface roughness measurements were taken at the end of each polishing session. As a main conclusion, it can be affirmed, regarding the force signal, that features extracted from both time and frequency domains are valuable data for the estimation of surface roughness.Publicación Surface Roughness Evaluation Based on Acoustic Emission Signals in Robot Assisted Polishing(MDPI, 2014-11-14) Agustina Tejerizo, Beatriz De; Marín Martín, Marta María; Teti, Roberto; Rubio Alvir, Eva María; MDPIThe 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.Publicación Analysis of Force Signals for the Estimation of Surface Roughness during Robot-Assisted Polishing(MDPI, 2018-08-15) Teti, Roberto; Agustina Tejerizo, Beatriz De; Marín Martín, Marta María; Rubio Alvir, Eva MaríaIn this study feature extraction of force signals detected during robot-assisted polishing processes was carried out to estimate the surface roughness during the process. The purpose was to collect significant features from the signal that allow the determination of the end point of the polishing process based on surface roughness. For this objective, dry polishing turning tests were performed on a Robot-Assisted Polishing (RAP) machine (STRECON NanoRAP 200) during three polishing sessions, using the same polishing conditions. Along the tests, force signals were acquired and offline surface roughness measurements were taken at the end of each polishing session. As a main conclusion, it can be affirmed, regarding the force signal, that features extracted from both time and frequency domains are valuable data for the estimation of surface roughness.