Seminar by Yaqiang Jin

Automated diagnosis of rolling element bearings based on explicit-duration hidden Markov model

As crucial components, rolling element bearing serves in all kinds of rotating mechanical systems, e.g., wind turbine, aerospace, transportation etc. Therefore the diagnosis of rolling element bearings is of importance to guarantee normal performance and security. Vibration signals generated by the rolling element bearings are known to carry useful diagnosis information. In this presentation,  one probabilistic model is introduced firstly to model the  nonstationary vibration signals. Then using the model parameters to achieve the proposed automated diagnosis framework that integrates fault detection, fault type identification and fault size quantification.

This seminar will be held online. Click here to join the Zoom event.