Cyclostationary-based tools for bearing diagnostics

Rolling element bearings are among the most common components which lead to machinery breakdown. Lately, focus has been targeted to cyclostationary-based tools that show a good performance in describing and detecting the bearing vibration signatures and early damage diagnosis. The Cyclic Spectral Correlation (CSC) and Coherence (CSCoh) describe the signal in terms of frequency-frequency content, detecting the hidden modulations and their carriers. Their integration results in an equivalent band-pass filtering and demodulation of the signal. Angular resampling methods are also applicable on the CSC or CSCoh, resulting in the signature description in the order-frequency or order-order domain. In this paper different methodologies for bearing fault detection based on CSC tools are presented. An optimization criterion is proposed in order to select the optimum integration limits. The methodologies are evaluated and compared in terms of performance on a number of real data.