Time and frequency domain scanning fault diagnosis method based on spectral negentropy and its application

Rolling bearings are one of the most important components in rotating machinery. It is important to accurately determine the center frequency and bandwidth of the resonant frequency band for bearing fault diagnosis. There are two problems with the existing methods for extracting bearing fault characteristics. First, due to the unreasonable spectrum segmentation, the determined resonant frequency band contains only partial fault information or hidden irrelevant information. Finally, because of the interference of the accidental impact, the correct fault characteristic information cannot be extracted. To solve the above problems, a time-frequency domain scanning empirical spectral negentropy method (T-FSESNE) based on spectral negentropy (NE) and empirical wavelet transform (EWT) is proposed in this paper. The signal is filtered twice by EWT filter: Firstly, the central frequencies of all resonance side bands are determined by using frequency-domain spectral negentropy, and then the optimal bandwidth of the resonance side bands is determined by using time-domain spectral negentropy. According to the determined center frequency and bandwidth, each component is extracted and analyzed by envelope spectrum to realize bearing fault diagnosis. The validity of the extracted methods is verified by bearing fault simulation and experimental signals. The results show that not only the interference of accidental impact can be effectively avoided but also the optimal center frequency and bandwidth can be determined quickly and accurately. More importantly, this method can determine the position of multiple resonance sidebands, which is more suitable for the analysis of complex fault vibration signals in rolling bearings.