Fault diagnosis of wind turbines under nonstationary conditions based on a novel tacho-less generalized demodulation

Dongdong Liu, Lingli Cui and Weidong Cheng

Renewable Energy, 2023, vol. 206, issue C, 645-657

Abstract: 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.

Keywords: fault diagnosis; Wind turbine; Frequency demodulation; Tacho-less; Nonstationary condition (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:206:y:2023:i:c:p:645-657

DOI: 10.1016/j.renene.2023.01.056

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