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Methodology for automatic selection of passes in surface grinding

Authors: Dotto, Fábio R. L.; Aguiar, Paulo Roberto de; Thomazella, Rogério; Bianchi, Eduardo Carlos;

Methodology for automatic selection of passes in surface grinding

Abstract

The main purpose of this work is the development of computational tools in order to assist the on-line automatic detection of burn in the surface grinding process. Most of the parameters currently employed in the burning recognition (DPO, FKS, DPKS, DIFP, among others) do not incorporate routines for automatic selection of the grinding passes, therefore, requiring the user’s interference for the choice of the active region. Several methods were employed in the passes extraction; however, those with the best results are presented in this article. Tests carried out in a surface-grinding machine have shown the success of the algorithms developed for pass extraction. Keywords: grinding process, computational tools, burning, acoustic emission, power signal

Keywords

670, computational tools, Grinding processes, Burning, Computer aided software engineering, Grinding process, Power signal, Acoustic emission, Power signals, Automation, power signal, Computational methods, Feature extraction, Automatic detection, grinding process, acoustic emission, Computational tools, Algorithms, Grinding (machining), burning

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
hybrid