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http://dx.doi.org/10.3795/KSME-A.2003.27.4.537

Fault Detection and Damage Pattern Analysis of a Gearbox Using the Power Spectra Density and Artificial Neural Network  

Lee, Sang-Kwon (인하대학교 기계공학과)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.27, no.4, 2003 , pp. 537-543 More about this Journal
Abstract
Transient vibration generated by developing localized fault in gear can be used as indicators in gear fault detection. This vibration signal suffers from the background noise such as gear meshing frequency and its harmonics and broadband noise. Thus in order to extract the information about the only gear fault from the raw vibration signal measured on the gearbox this signal is processed to reduce the background noise with many kinds of signal-processing tools. However, these signal-processing tools are often very complex and time waste. Thus. in this paper. we propose a novel approach detecting the damage of gearbox and analyzing its pattern using the raw vibration signal. In order to do this, the residual signal. which consists of the sideband components of the gear meshing frequent) and its harmonics frequencies, is extracted from the raw signal by the power spectral density (PSD) to obtain the information about the fault and is used as the input data of the artificial neural network (ANN) for analysis of the pattern of gear fault. This novel approach has been very successfully applied to the damage analysis of a laboratory gearbox.
Keywords
Fault Detection; Gear Box; Pattern Analysis; Neural Network;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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