Application of Feature Extraction Method Based on Empirical Fourier Decomposition in Rotor Rub-impact Fault

Abstract This paper provides a feature extraction technique primarily by using empirical Fourier decomposition (EFD) to reveal the time-frequency features of rotor rub-impact fault. The Hilbert transform estimates the instantaneous frequency (IF) and instantaneous amplitude (IA) of the signal generated by EFD. Finally, high-quality time-frequency representation (TFR) is reconstructed by the adaptive time-frequency spectrum (ATFS). An example of the rotor rub-impact fault is utilized to demonstrate efficiency of this technique, and the results are contrasted with those of empirical mode decomposition (EMD). EFD performs better in the modal mixing problem than EMD and has excellent decomposition efficiency. It realizes IF feature extraction and offers a more precise TFR.