Second-Order Multisynchrosqueezing Wavelet Transform for Bearing Fault Detection

Propose Vibration responses generated by defective bearing under variable speed are nonstationary signals with strong modulation features. Accurately extracting the fault-related features from such signals is a challenging task in the fault diagnosis of bearing. In this paper, a new multiple squeezing method based on the wavelet transform is proposed to address this issue. Methods The proposed method employs the second-order instantaneous frequency (IF) estimate to approximate the true IF of the analyzed signal, and then iteratively conducts the multiple squeezing operations to reallocate the non-reassigned points caused by the inaccurate IF estimate. Results This method can achieve a high-quality time-frequency representation with multiple resolutions for nonstationary signals with strongly nonlinear IF, and retain good signal reconstruction ability even in noisy environment. Simulation and real-world signals are used to verify the superiority of the proposed method with respect to other advanced time-frequency analysis (TFA) methods. Conclusion The analysis results confirm that the proposed method is more effective for characterizing strongly nonstationary vibration signals and fault detection in practical application.