Performance Analysis of an EEMD-based Hilbert Huang Transform as a Bearing Failure Detector in Wind Turbines

Yassine Amirat (1) , Mohamed Benbouzid (1) , Tianzhen Wang (2) , Sylvie Turri (1)

1 LBMS - Laboratoire brestois de mécanique et des systèmes
2 Shanghai Maritime University

Sustainability and viability of wind farms are highly dependent on the reduction of the operational and maintenance costs. The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the degeneration of the generator health, facilitating a proactive response, minimizing downtime, and maximizing productivity. This paper deals then with the assessment of a demodulation technique for bearing failure detection through wind turbines generator stator current. The proposed technique is based on a modified version of the Hilbert Huang transform. In this version, the use of the EEMD algorithm allows overcoming the well-known mixed mode.

Mots clés: Wind turbines; bearing failure detection; amplitude demodulation; Hilbert Huang transform; EEMD

Domaines: Energie électrique

Yassine Amirat, Mohamed Benbouzid, Tianzhen Wang, Sylvie Turri. Performance Analysis of an EEMD-based Hilbert Huang Transform as a Bearing Failure Detector in Wind Turbines. IEEE ICGE 2014, Mar 2014, Sfax, Tunisia. pp.193-198. ⟨hal-01023502⟩