Fault diagnosis of rolling element bearings with a spectrum searching method

Rolling element bearing faults in rotating systems are observed as impulses in the vibration signals, which are usually buried in noise. In order to effectively detect faults in bearings, a novel spectrum searching method is proposed in this paper. The structural information of the spectrum (SIOS) on a predefined frequency grid is constructed through a searching algorithm, such that the harmonics of the impulses generated by faults can be clearly identified and analyzed. Local peaks of the spectrum are projected onto certain components of the frequency grid, and then the SIOS can interpret the spectrum via the number and power of harmonics projected onto components of the frequency grid. Finally, bearings can be diagnosed based on the SIOS by identifying its dominant or significant components. The mathematical formulation is developed to guarantee the correct construction of the SIOS through searching. The effectiveness of the proposed method is verified with both simulated and experimental bearing signals.