Title of article
Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis
Author/Authors
Junsheng Cheng، نويسنده , , Dejie Yu، نويسنده , , Jiashi Tang، نويسنده , , Yu Yang، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2008
Pages
12
From page
712
To page
723
Abstract
Targeting the advantages of Hilbert–Huang transform (HHT) and the characteristics of gear fault vibration signals, HHT is introduced into gear fault diagnosis. The concept of local Hilbert energy spectrum is proposed and two gear fault diagnosis approaches, namely, frequency family separation method based on EMD (empirical mode decomposition) and local Hilbert energy spectrum method, are put forward, which are applied to gear fault diagnosis. Considering that the gear fault vibration signal is a multi-component amplitude-demodulated and frequency-demodulated (AM–FM) signal and EMD could exactly decompose the AM–FM signal into a number of intrinsic mode functions (IMFs), each of which can be amplitude-demodulated or frequency-demodulated component, the frequency families could be separated effectively from the gear vibration signal by applying EMD to the gear vibration signal. Furthermore, when faults occur in gear, the energy of the gear vibration signal would change correspondingly, whilst the local Hilbert energy spectrum can exactly provide the energy distribution of the signal in certain frequency with the change of the time and frequency. Thus, the fault information of the gear vibration signal can be extracted effectively from the local Hilbert energy spectrum. The analysis results from the experimental signals show that both frequency family separation method based on EMD and local Hilbert energy spectrum method could extract the characteristics information of the gear fault vibration signal effectively.
Keywords
Frequency family , Local Hilbert energy spectrum , Gear , Fault diagnosis , Empirical mode decomposition (EMD) , Intrinsic mode functions (IMFs) , Hilbert–Huang Transform
Journal title
Mechanism and Machine Theory
Serial Year
2008
Journal title
Mechanism and Machine Theory
Record number
1163995
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