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Annual Conference of the PHM Society
Article . 2010 . Peer-reviewed
License: CC BY
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IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
Article . 2012 . Peer-reviewed
License: IEEE Copyright
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Article . 2012
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Gear Fault Location Detection for Split Torque Gearbox Using AE Sensors

Authors: Ruoyu Li 0001; Serap Ulusam Seçkiner; David He; Eric Bechhoefer; Praneet Menon;

Gear Fault Location Detection for Split Torque Gearbox Using AE Sensors

Abstract

In comparison with a traditional planetary gearbox, the split torque gearbox (STG) potentially offers lower weight, increased reliability, and improved efficiency. These benefits have driven helicopter OEMs to develop products using STG. However, the effect of multiple gears meshing simultaneously with the central gear and a large number of synchronous components (gears or bearing) in close proximity creates a problem on how to detect the gear fault location in a STG. As of today, only limited research on STG fault detection using vibration sensors and acoustic emission sensors has been conducted.In this paper, an effective methodology on gear fault location detection using AE sensors for STG is presented. The methodology uses wavelet transform to process the AE sensor signals to determine the arrival time of the AE bursts at different locations. By analyzing the arrival times of the AE bursts, the gear fault location can be determined. The parameters of the wavelet transform are optimized by using an ant colony optimization algorithm. Real seeded gear fault experimental tests on a notational STG are conducted. AE sensor signals at the locations of healthy and damaged output driving gears are collected simultaneously to determine the location of the damaged gear. Experimental results have shown the effectiveness of the presented methodology.

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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).
    30
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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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!
30
Top 10%
Top 10%
Average
hybrid