Application of the horizontal slice of cyclic bispectrum in rolling element bearings diagnosis
The vibration signals of rolling element bearings are random cyclostationary when they have faults. However, because the background noise is very heavy when the early fault occurs, it is difficult to disclose the latent periodic components successfully even using the second order cyclostationary analysis. To overcome this difficulty, the cyclic bispectrum (CBS), an alternative approach based on bispectrum and cyclostationarity analysis, is discussed in this paper. Furthermore, the slice spectrum analysis of the CBS is proposed. The CBS is a third-order cyclic statistical parameter, in the frequency domain. The CBS gives full play to the advantage, which is provided from the higher order cyclic statistical methods. It can restrain noise and provide more information than classical methods such as amplitude spectrum analysis and envelope analysis when the fault is at an early stage. However, the CBS is four-dimensional. So, the Slices Spectrum Analysis of the CBS is introduced to fault diagnosis. Firstly, the slice of the CBS, which is 3D structure, is sliced along the cyclic frequency axis. The CBS corresponding to one cyclic frequency is called the once slice of the CBS. However the information in the once slice is redundant and indirect for fault diagnosis. So the twice slice of the CBS, which is sliced along one frequency axis is studied. By analysis, the horizontal slice of the once slice of the CBS (HSCBS), which is at a special given cyclic frequency is proposed to resolve the contradiction. Simulation and experiment of the rolling element bearing fault diagnosis are performed, and the results indicate the feasibility and validity of the HSCBS analysis in rolling element bearing early fault diagnosis.
cyclic bispectrum rolling element bearing fault diagnosis