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Author:

Liu, D. (Liu, D..) | Cui, L. (Cui, L..) | Cheng, W. (Cheng, W..)

Indexed by:

EI Scopus SCIE

Abstract:

The fault diagnosis of wind turbines under nonstationary conditions is still challenging. This paper proposes a novel tacho-less generalized demodulation (NTLGD) method for the wind turbine fault diagnosis. First, one instantaneous frequency is extracted from the time-frequency representation of the vibration signal. Second, a novel phase function design method is developed based on the extracted frequency, by which, different from traditional methods, the fault-related frequencies are mapped into the fixed predefined values. Then, the bandpass filters are designed according to the designed phase functions to separate the mapped frequencies. Finally, the diagnosis template is constructed, and the fault is localized by matching the peaks in the demodulated spectrum with the spectral lines in the template. The method is evaluated by the vibration signals of support bearings and the planetary gearbox in a test rig of wind turbine drive train. The results demonstrate that the proposed method can well pinpoint the fault-related frequency components without a tachometer and the demodulated values are independent of speed profiles. © 2023

Keyword:

Tacho-less Wind turbine fault diagnosis Frequency demodulation Nonstationary condition

Author Community:

  • [ 1 ] [Liu D.]Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Cui L.]Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Cheng W.]School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, 100044, China

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Source :

Renewable Energy

ISSN: 0960-1481

Year: 2023

Volume: 206

Page: 645-657

8 . 7 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:19

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 33

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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