Higher-Order Spectra Analysis-Based Diagnosis Method of Blades Biofouling in a PMSG Driven Tidal Stream Turbine

Most electrical machines and drive signals are non-Gaussian and are highly nonlinear in nature. A useful set of techniques to examine such signals relies on higher-order statistics (HOS) spectral representations. They describe statistical dependencies of frequency components that are neglected by tr...

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Bibliographic Details
Published inEnergies (Basel) Vol. 13; no. 11; p. 2888
Main Authors Saidi, Lotfi, Benbouzid, Mohamed, Diallo, Demba, Amirat, Yassine, Elbouchikhi, Elhoussin, Wang, Tianzhen
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.06.2020
MDPI
Subjects
Biofouling
bispectrum
Corrosion
Diagnosis
Electric power
Electricity
Energy
Engineering Sciences
Fault diagnosis
Kurtosis
Marine environment
Noise
Permanent magnets
Power
Rotor blades
Rotor blades (turbomachinery)
Signal processing
Spectra
spectral kurtosis
Statistical analysis
stator current
tidal stream turbine
Turbine blades
Turbines
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Summary:Most electrical machines and drive signals are non-Gaussian and are highly nonlinear in nature. A useful set of techniques to examine such signals relies on higher-order statistics (HOS) spectral representations. They describe statistical dependencies of frequency components that are neglected by traditional spectral measures, namely the power spectrum (PS). One of the most used HOS is the bispectrum where examining higher-order correlations should provide further details and information about the conditions of electric machines and drives. In this context, the stator currents of electric machines are of particular interest because they are periodic, nonlinear, and cyclostationary. This current is, therefore, well adapted for analysis using bispectrum in the designing of an efficient condition monitoring method for electric machines and drives. This paper is, therefore, proposing a bispectrum-based diagnosis method dealing the with tidal stream turbine (TST) rotor blades biofouling issue, which is a marine environment natural process responsible for turbine rotor unbalance. The proposed bispectrum-based diagnosis method is verified using experimental data provided from a permanent magnet synchronous generator (PMSG)-based TST experiencing biofouling emulated by attachment on the turbine blade. Based on the achieved results, it can be concluded that the proposed diagnosis method has been very successful. Indeed, biofouling imbalance-related frequencies are clearly identified despite marine environmental nuisances (turbulences and waves).
ISSN:1996-1073
1996-1073
DOI:10.3390/en13112888