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conferencePaper IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 1 DOI 10.1109/IECON.2019.8926625 Saidi Lotfi Benbouzid Mohamed Diallo Demba Amirat Yassine Elbouchikhi Elhoussin Wang Tianzhen Bispectrum Blades Frequency measurement Generators Rotors Stators Wind turbines biofouling spectral kurtosis stator current tidal turbine turbulence wave PMSG-based Tidal Current Turbine Biofouling Diagnosis using Stator Current Bispectrum Analysis Most of signals in the electrical machines and drives are non-Gaussian and highly nonlinear in nature. A useful set of techniques for examining these kinds of signals relies on the spectral representations of higher-order statistics (HOS), well-known as polyspectra. They describe statistical dependences of frequency components that are neglected by traditional spectral measures. The bispectrum is the most used HOS, and studying higher-order correlations provides more information about the electromechanical system's behavior. It helps in building more accurate diagnostic models. Based on this proper relationship the overall aim of the current work is the interpretation of the stator current tidal turbine bispectrum under imbalanced rotor blades condition. Based on this proper relationship, the overall aim of the current work is the interpretation of the permanent magnet synchronous generator (PMSG)-based tidal current turbine (TCT) stator current bispectrum for the diagnosis of biofouling. The proposed bispectrum-based diagnosis method has been tested using experimental data issued from a TCT experiencing biofouling emulated by an attachment on the turbine rotor. The achieved results clearly indicate the feasibility and efficacy of the proposed method. October 2019 IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 6998-7003 IEEE Xplore ISSN: 1553-572X