Fault Feature Extraction of Rolling Element Bearing under Complex Transmission Path Based on Multiband Signals Cross-Correlation Spectrum

Aiming at the problem that bearing fault signals are influenced by complex transmission path and multiple structures of equipment, which results in strong interference components, a fault feature extraction approach for rolling element bearing based on multiband signals cross-correlation spectrum was proposed. First, the improved trend-line method was utilized to improve the calculation efficiency and the influence of the transmission path was removed. Second, the optimal and suboptimal analysis frequency bands were selected with the maximum energy ratio of the feature components as the objective function, which further suppresses the interference of irrelevant components and avoids the blindness selection of the analysis band. Finally, with the advantage of the cross-correlation spectrum, the optimal band signals were combined for analysis to enhance the fault signatures. The simulation signal and the measured bearing inner race and outer race defect signals were utilized for verification; with the help of comparisons, the results indicate that the method in this paper can effectively remove the influence of complex transmission path and accurately extract the bearing fault features from the strong background interference.