Damage mechanics approach for bearing lifetime prognostics

By J. Qiu, B. Seth, Steven Y. Liang, Cheng Zhang. 2002

159 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/1ba6211d1a0558d62c95320f704207c2209c41c5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Noureddine Zerhouni
2. Kamal Medjaher
3. Robert X. Gao
4. Diego Alejandro Tobon-Mejia
5. David A. Dornfeld
6. Soundar Kumara *
7. M. Mori
8. Gerard Tripot

In Mechanical Engineering

1. Noureddine Zerhouni
2. Kamal Medjaher
3. Diego Alejandro Tobon-Mejia
4. Robert X. Gao
5. David A. Dornfeld
6. Soundar Kumara *
7. M. Mori
8. Gerard Tripot

Citations in the corpus

• Cloud-enabled prognosis for manufacturing (2015, background): “[65] developed a stiffness-based model to achieve accurate bearing prognosis considering the bearing system as single-degree-offreedom system with its natural frequency related to the system stiffness.”
• A Data-Driven Failure Prognostics Method Based on Mixture of Gaussians Hidden Markov Models (2012, background): “[20] proposed a prognostics model to estimate the RUL on bearings.”