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Analysis of Force Signals for the Estimation of Surface Roughness during Robot-Assisted Polishing

机译:用于评估机器人抛光过程中表面粗糙度的力信号分析

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摘要

In 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.
机译:在这项研究中,对在机器人辅助抛光过程中检测到的力信号进行了特征提取,以估算过程中的表面粗糙度。目的是从信号中收集重要特征,这些特征允许根据表面粗糙度确定抛光过程的终点。为此目的,在三个抛光阶段中,使用相同的抛光条件,在机器人辅助抛光(RAP)机器(STRECON NanoRAP 200)上进行了干抛光车削测试。沿着测试,获取力信号,并在每次抛光结束时进行离线表面粗糙度测量。作为一个主要结论,关于力信号,可以肯定的是,从时域和频域中提取的特征对于评估表面粗糙度是有价值的数据。

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