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Signal model of a cycloidal drive for diagnostic purposes

Authors: Pasquale Grosso; Giulia Massaccesi; Jacopo Cavalaglio Camargo Molano; Giovanni Mottola; Davide Borghi;

Signal model of a cycloidal drive for diagnostic purposes

Abstract

The study of gearboxes for diagnostic and prognostic purposes plays a major role in industrial applications, especially in the robotics and automation fields, where such devices are used extensively. The present work has been focused on the cycloidal drives, which are widely adopted thanks to their compactness and sturdiness, nevertheless they present a complex architecture. An analytical model of the vibrational behaviour of such a device has been developed aiming to obtain an efficient simulation tool, able to consider different faults occurring due to the natural wear of components. The model has been obtained thanks to a positional angular-based method giving the contacts patterns construction as a time-independent function, thus any input speed profile can be taken into account. Internal loads distribution has been a crucial aspect of the modelling, also needed in order to provide an estimate of the machine efficiency. This simulation tool may be finally generalized in order to extend the analysis capability to the epicyclic gear train family.

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selected citations
These citations are derived from selected sources.
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!
0
Average
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Green