A novel generalized Vold-Kalman filtering for wind turbine fault diagnosis

Abstract

Fault diagnosis of offshore wind turbines (WTs) is vital to the reliability and efficiency of wind power generation. Generalized demodulation has been demonstrated to be effective in revealing the fault-related frequencies, but there are intricate interfering components in the demodulation spectra due to the iterative demodulation operation and the complex modulation nature of vibration signals of WT. This paper develops a novel generalized Vold-Kalman filtering approach. To separate the signal components, Vold-Kalman filter is adopted to the amplitude envelope of vibration signal by exploiting its merit in non-component decomposition, in which a frequency set is constructed by the modulation nature of machinery vibration. The phase functions of the frequencies in the frequency set are constructed, by which the variable components are transformed into constant ones. The proposed method is tested via the data of rolling bearings and a WT planetary gearbox.