MetaTOC stay on top of your field, easily

A novel shift-invariant dictionary learning approach integrated with a hidden Markov model for diagnosing bearing faults in time-varying conditions

, , , ,

Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, Ahead of Print.
Bearing fault diagnosis is crucial for mechanical system reliability. Numerous techniques have been developed to identify faults in bearings. However, the signals under time-varying speed condition are nonstationary, and most diagnosis methods suffer from ...