A novel shift-invariant dictionary learning approach integrated with a hidden Markov model for diagnosing bearing faults in time-varying conditions
Published online on April 17, 2025
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 ...
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 ...