Development and evaluation of AE based condition indicators for full ceramic bearing fault diagnosis

Full ceramic bearings are considered the first step towards full ceramic, oil free engines in the future. No research on full ceramic bearing fault diagnostics using acoustic emission (AE) sensors has been reported. Unlike their steel counterparts, AE fault characteristic features of full ceramic bearings and effective signal processing methods for extracting these characteristic features have not been established. In this paper, the development and evaluation of AE based condition indicators (CIs) for full ceramic bearing fault detection and diagnosis are presented. The AE based CIs are developed using an empirical mode decomposition (EMD) based AE feature extraction method and evaluated by testing bearings with seeded outer race, inner race, ball, and cage faults on a bearing diagnostic test rig.