Paper Title:

Hilbert-Huang Transform and Its Application in Gear Faults Diagnosis

Periodical Key Engineering Materials (Volumes 291 - 292)
Main Theme Advances in Abrasive Technology VIII
Edited by Yury M. Baron, Jun'ichi Tamaki and Tsunemoto Kuriyagawa
Pages 655-660
DOI 10.4028/www.scientific.net/KEM.291-292.655
Citation H. Li et al., 2005, Key Engineering Materials, 291-292, 655
Online since August, 2005
Authors H. Li, H.Q. Zheng, L.W. Tang
Keywords Empirical Mode Decomposition (EMD), Fault Diagnosis, Gear, Hilbert-Huang Transform (HHT), Signal Processing
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Time-frequency and transient analysis have been widely used in signal processing and faults diagnosis. These methods represent important characteristics of a signal in both time and frequency domain. In this way, essential features of the signal can be viewed and analyzed in order to understand or model the faults characteristics. Historically, Fourier spectral analyses have provided a general approach for monitoring the global energy/frequency distribution. However, an assumption inherent to this method is the stationary and linear of the signal. As a result, Fourier methods are not generally an appropriate approach in the investigation of faults signals with transient components. This work presents the application of a new signal processing technique, empirical mode decomposition and the Hilbert spectrum, in analysis of vibration signals and gear faults diagnosis for a machine tool. The results show that this method may provide not only an increase in the spectral resolution but also reliability for the gear faults diagnosis.

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