Riesz Time-Frequency Spectrum Transform and Its Application in Rolling Bearing Fault Diagnosis

Traditional time-frequency analysis methods can only obtain the amplitude and frequency information in the time-frequency domain of the signal, making it difficult to comprehensively characterize fault feature when analyzing rolling bearing vibration signals. Therefore, this article introduces a novel time-frequency analysis method called the Riesz time-frequency spectrum transform (RTST). This method first proposes a new time-frequency analysis method, the Riesz four-parameter spectrum time-frequency analysis method, which is used to obtain the amplitude, frequency, phase, and orientation of the vibration signal in the time-frequency domain. Then, in order to select the optimal parameter spectrum, the symbol dynamics entropy (SDE) is expanded to two dimensions, and a new entropy calculation method, cosine SDE (CSDE), is proposed. Finally, the entropy-selected parameter spectrum is used to extract time-frequency ridges for time-frequency analysis, based on which the RTST method is proposed. Experimental demonstrate that the RTST method offers superior time-frequency concentration and robustness.