A rolling bearing fault diagnosis method based on wavelet packet energy spectrum and modulation signal bispectrum analysis. The method comprises the following steps: step I, measuring a vibration signal of a detected rolling bearing; step II, carrying out wavelet packet decomposition on the vibration signal to obtain frequency bands of a wavelet packet; step III, obtaining wavelet packet energy spectrums of frequency bands and carrying out normalization to obtain normalized frequency bands; step IV, selecting an energy-concentrated frequency band from among the normalized frequency bands to carry out signal reconstruction; and step V, carrying out modulation signal bispectrum analysis on a frequency band of a reconstructed signal to obtain the fault feature frequency of the rolling bearing. Combining the transient characteristic of WPE and the periodic characteristic of MSB effectively improves the effect of the bearing fault diagnosis. The method can accurately extract the fault feature frequency, achieves a high signal-to-noise ratio and has good application prospects in the field of rotating mechanical fault diagnosis.
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