کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
802651 904426 2008 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis
چکیده انگلیسی

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechanism and Machine Theory - Volume 43, Issue 6, June 2008, Pages 712–723
نویسندگان
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