A new fault detection strategy for wind turbine rotor imbalance based on multi-condition vibration signal analysis

Abstract

Aiming at the problem that it is difficult to accurately detect the position and magnitude of pitch angle deviation (PAD) fault of wind turbine (WT) in operation at the same time, this paper proposes a novel multi-parameter synergy mechanism based on a double threshold judgment method combined with power spectral density analysis. First, the influence of different PADs of a single blade on the time domain information of WT parameters under different turbulent wind speeds is discussed. Second, according to the changing rule of three blade parameters caused by the single blade PAD, the double threshold judgment method is introduced to determine the faulty blade and the direction of PAD. Third, this paper put forward the concept of characteristic frequency power ratio. Based on the characteristic frequency of the power spectrum, a method is proposed to determine the magnitude of PAD. Finally, a complete set of fault detection and identification flow for single blade PAD was established. This detection strategy is more accurate and faster than the traditional methods and does not need to add additional data acquisition equipment in the wind power generation system.