2005
DOI: 10.1016/j.ymssp.2004.02.007
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Cyclostationarity analysis for gearbox condition monitoring: Approaches and effectiveness

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Cited by 73 publications
(28 citation statements)
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“…where x is the mean value of x and r is the standard deviation of x. : ð28Þ (5) The RMS value of the first IMF C 1 that is decomposed from the vibration measurement. (6) The range value of the first IMF C 1 that is decomposed from the vibration measurement.…”
Section: Intelligent Diagnosis Of Faulted Gearsmentioning
confidence: 99%
See 1 more Smart Citation
“…where x is the mean value of x and r is the standard deviation of x. : ð28Þ (5) The RMS value of the first IMF C 1 that is decomposed from the vibration measurement. (6) The range value of the first IMF C 1 that is decomposed from the vibration measurement.…”
Section: Intelligent Diagnosis Of Faulted Gearsmentioning
confidence: 99%
“…Among the previous literature, Randall [1,2] provided complete and systematic review for summarizing the measurement techniques as well as the fault diagnosis of bearing and gearbox systems. Owing to the nature of periodicity in rotational machines, the cyclostationarity analysis has been employed to diagnose the defective gears and other malfunctions in rotating machinery [3][4][5]. Since the defective portion impacts upon another components of rotary system and produces the amplitude-modulated vibration, the envelope analysis and the demodulation technique are also widely utilized for fault diagnosis of rotating machinery [4,6,7].…”
Section: Introductionmentioning
confidence: 99%
“…The common types of gear damage mainly consist of pitting, scuffing, spalling, cracking and wear. One of the major reasons for gear fault is excessive vibration [6]. Extensive literature is available on diagnosing rolling element bearing defects using vibration analysis.…”
Section: Introductionmentioning
confidence: 99%
“…However, localized defects in rotary machinery parts tend to result in multiple impulse responses, which are generally cyclic impulse responses. Considering that the waveform of Morlet wavelet is in shape similar to transient vibration caused by gearbox localized defects [7,8] and cyclostationarity matches the key feature of the gearbox vibration [9,10], Cyclic Morlet Wavelet Correlation Filtering (CMWCF) is thus proposed, which based on correlation filtering, construct the cyclic Morlet wavelet and identify both the impulse response parameters and the cyclic period for diagnose gear fault.…”
Section: Introductionmentioning
confidence: 99%