| Citation: | WANG Hongwei, GUO Yu, ZHONG Hui, et al. Rolling bearing fault detection based on cyclic spectral coherence of IAS signals[J]. Journal of Aerospace Power, 2025, 40（12）：20230497 doi: 10.13224/j.cnki.jasp.20230497
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In order to address the challenge of selecting frequency bands with abundant fault information in cyclic spectral coherence (CSCoh), the advantages of encoder signals were combined, and instantaneous angular speed (IAS) was taken as the signal source to propose a method for adaptive determination of CSCoh optimized demodulation bands based on the reweighted kurtosis (RK) index. The forward differential method was employed to estimate the IAS signal based on the instantaneous angular displacement information from the encoder. CSCoh analysis was performed to extract the fault-related components of rolling bearings, and a bivariate spectrum composed of cycle order and spectral order was obtained. Subsequently, an improved envelope spectrum (IES) was obtained by integrating along the spectral order. The RK index was used to characterize the richness of rolling bearing fault information in each sub-band. The sub-band was combined and reconstructed along the spectral order axis, and the combined sub-band corresponding to the maximum RK value after the merger reconstruction was selected as the optimized demodulation band. Envelope analysis was conducted to reveal the bearing fault characteristics. By analyzing the simulation signals and experimental data with the method proposed and comparing with the existing methods, the proposed method can effectively extract the fault characteristics of the inner and outer rings of rolling bearing.
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