Feature extraction of rotor-stator rubbing faults based on harmonic fusion vector bispectrum, ITD and Hjorth parameters

Abstract

To solve the difficulty in extracting the characteristics of rotor–stator rubbing faults, the paper has proposed the combined method of Complexity parameter, the harmonic fusion vector bispectrum (HFVB), and intrinsic time-scale decomposition (ITD). First, to fully embody the characteristic information of fault, the HFVB is used to blend the information of signals collected from sensors installed in different positions. Second, taking in mind that the ITD algorithm can embody the effective separation of nonstationary and nonlinear signals, the ITD algorithm makes the separation of blended signals. Third, regarding the important influence of signal complexity on fault characteristic extraction, the complexity parameter of Hjorth parameters can provide very great embodiment of signal complexity. Complexity parameter of Hjorth parameters is introduced as a characteristic parameter index to make a option of proper rotation component (PRC) which can show the characteristics of rubbing fault better. Fourth, signals are reconstructed based on chosen signal components. Meanwhile, to reduce the influence of noise, reconstructed signals are denoised accordingly. Finally, implement the characteristic extraction and fault identification of rubbing faults according to the square demodulation spectrum (SDF) of denoised signals. The result indicates that the harmonic fusion vector bispectrum method can embody the effective blending of fault information; the complexity parameter in Hjorth parameter can serve as the index parameter for option of sensitive characteristic components of rubbing faults. Based on the proposed method, in the square demodulation spectrum of reconstructed signals, it can effectively and precisely provide the characteristics of rotor–stator rubbing fault and successfully identify a fault type.8714542030