2012
DOI: 10.1109/tsmcc.2011.2182609
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Gear Fault Location Detection for Split Torque Gearbox Using AE Sensors

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Cited by 31 publications
(14 citation statements)
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“…The motors respond to 3 pair of poles at 6000 rpm and 2.3 Nm of rated speed and torque respectively. A commercial AE transducer, Vallen-Systeme VS900-M, covering the spectral band of interest from 50 kHz to 500 kHz, is located in contact with the gearbox casing as close as possible to the shaft as proposed in similar works [28], [29].…”
Section: Resultsmentioning
confidence: 99%
“…The motors respond to 3 pair of poles at 6000 rpm and 2.3 Nm of rated speed and torque respectively. A commercial AE transducer, Vallen-Systeme VS900-M, covering the spectral band of interest from 50 kHz to 500 kHz, is located in contact with the gearbox casing as close as possible to the shaft as proposed in similar works [28], [29].…”
Section: Resultsmentioning
confidence: 99%
“…With the quadratic detector the significant detection features can be selected automatically and the final detection results are nearly perfect. Li et al [52] defined an effective gear fault location detection methodology using Acoustic Emission (AE) sensors for splitting torque gearbox by analyzing the arrival time of the AE bursts to determine the gear fault location. Siegel et al [83,84] proposed a methodology for predicting helicopter rolling element bearing failure in which a series of processing steps in prior, including feature extraction, feature selection, and health assessment are included.…”
Section: Manned Helicoptersmentioning
confidence: 99%
“…Qi and Han [17] proposed a novel wavelet-based approach to detect an abrupt fault in UH sensor system. Li et al [36] defined an effective gear fault location detection methodology using Acoustic Emission (AE) sensors for splitting torque gearbox by analyzing the arrival time of the AE bursts to determine the gear fault location. Waschburger et al [37] presented an experimental validation of wavelet-based analytical redundancy technique on a 3DOF UH platform.…”
Section: A Analytical Model-based Approachesmentioning
confidence: 99%