2014
DOI: 10.3390/s140101372
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Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study

Abstract: In recent years, acoustic emission (AE) sensors and AE-based techniques have been developed and tested for gearbox fault diagnosis. In general, AE-based techniques require much higher sampling rates than vibration analysis-based techniques for gearbox fault diagnosis. Therefore, it is questionable whether an AE-based technique would give a better or at least the same performance as the vibration analysis-based techniques using the same sampling rate. To answer the question, this paper presents a comparative st… Show more

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Cited by 105 publications
(57 citation statements)
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“…They explain that factors like temperature of the lubrication can have significant effect on acoustic emission. However, Qu et al [97] compared vibration and acoustic emission data from wind turbine drivetrain for detection of gear tooth crack. They concluded that the AE technique is less susceptible to background mechanical noise than vibration sensing and is more sensitive to tooth damage in low rotational speeds.…”
Section: Acoustic Emission Signaturementioning
confidence: 99%
“…They explain that factors like temperature of the lubrication can have significant effect on acoustic emission. However, Qu et al [97] compared vibration and acoustic emission data from wind turbine drivetrain for detection of gear tooth crack. They concluded that the AE technique is less susceptible to background mechanical noise than vibration sensing and is more sensitive to tooth damage in low rotational speeds.…”
Section: Acoustic Emission Signaturementioning
confidence: 99%
“…After TSA is computed, any kind of fault diagnostic CIs can be evaluated. Although successful TSA applications to many types of signals such as vibration and acoustic emission signals have been reported in the literature [40], [41], application of TSA to PE strain signal processing for PGB fault diagnosis has not yet been reported.…”
Section: A Tsamentioning
confidence: 99%
“…He et al [11] proposed a data mining-based diagnostic system using acoustic emission (AE) signals to detect faults in full ceramic bearings. They further developed a series of methods to identify faults in plastic bearings [12], gearbox tooth cut faults [13], planetary gearbox faults [14], etc.…”
Section: Introductionmentioning
confidence: 99%