Name
Title | ||
|---|---|---|
An Integrated Bayesian Approach To Prognositics Of The Remaining Useful Life And Its Application On Bearing Degradation Problem |
Abstract | ||
|---|---|---|
Degradation information of a complex mechanical system reflects the system's health status and is useful to predict the future progression of the fault or anomalous behaviors. This paper proposed a two-stage strategy to predict the future health status of a bearing by utilizing the bearing's degradation information. The first stage was implemented to monitor the bearing's health status until a degradation point was detected. When the bearing begins to degrade, a prediction stage based on Kalman filter was then used to estimate the remaining useful life (RUL) of the bearing. Finally, a real bearing degradation problem was used to verify our method. |
Year | Venue | Keywords |
|---|---|---|
2015 | PROCEEDINGS 2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN) | Degradation, Kalman filter, RUL estimation, Prognostics |
Field | DocType | ISSN |
Degradation Problem,Kalman filter,Bearing (mechanical),Condition monitoring,Engineering,Reliability engineering,Mechanical system,Bayesian probability | Conference | 1935-4576 |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Wang | 1 | 29 | 3.82 |
| Yizhen Peng | 2 | 22 | 2.00 |
| Yanyang Zi | 3 | 268 | 25.13 |
| Xiaohang Jin | 4 | 49 | 3.92 |
| K. Leung | 5 | 487 | 67.33 |