A fault diagnosis methodology for rolling element bearings based on advanced signal pretreatment and autoregressive modelling

• Published in: Journal of sound and vibration Vol. 369; pp. 246 - 265
• Main Authors: Al-Bugharbee, Hussein, Trendafilova, Irina
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 12.05.2016
• Subjects: Accuracy; Autoregressive processes; Bearings; Diagnosis; Fault diagnosis; Invariants; Linear autoregressive modelling; Methodology; Pattern recognition; Pretreatment; Rolling element bearings; Singular spectrum analysis; Stationarisation; Fault diagnosis; Linear autoregressive modelling; Singular spectrum analysis; Rolling element bearings; Pattern recognition; Stationarisation

This study proposes a methodology for rolling element bearings fault diagnosis which gives a complete and highly accurate identification of the faults present. It has two main stages: signals pretreatment, which is based on several signal analysis procedures, and diagnosis, which uses a pattern-reco...