Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency Estimation

Abstract

The fault vibration signal of rotating machinery system under strong background noise has the characteristics of non-stationary, non-Gaussian and complex components. In view of these characteristics, an improved method of signal separation based on Vold-Kalman filter (VKF) of adaptive instantaneous frequency estimation is proposed. First, a method for adaptive multiridge extraction of peaks detection based on synchro-squeezing wavelet transform (SWT) is proposed as the high-precision adaptive instantaneous frequency (IF) estimation method. The high precision IF estimation is used as the instantaneous frequency parameter of VKF, so that the complex multi-component non-stationary signal can be separated directly in the time domain and transformed into a signal combination composed of multiple stationary single-component signals and signal residues. Secondly, an improved method is proposed combining the adaptive IF estimation method with order tracking analysis and diagonal slice of bispectrum. In the improved method, the corresponding IF estimation of each component signal is taken as the reference frequency of its order tracking and the order spectrum analysis of each component signal is carried out respectively. Meanwhile, the signal residual is analyzed by diagonal slice of bispectrum, so as to suppress Gaussian noise and effectively separate and extract fault features in the vibration signal. Finally, the method is verified on simulation data and experimental data under different conditions. The results show that the improved method has higher extraction accuracy than other traditional methods. It has the superiority and the great potential for practical applications.