Name
Abstract | ||
|---|---|---|
In this paper, we propose a method for online assessing the performance of a prognostic approach in situations of very poor knowledge on the degradation process. In particular, we deal with cases in which the entire degradation process, from the beginning of the operation until failure, has never been observed and, thus, the traditional offline performance metrics cannot be applied. The proposed m... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TR.2015.2500681 | IEEE Transactions on Reliability |
Keywords | Field | DocType |
Degradation,Hidden Markov models,Capacitors,Turbines,Blades,Biological system modeling,Time measurement | Capacitor,Kernel smoother,Turbine blade,Particle filter,Hidden Markov model,Degradation process,Mathematics,Reliability engineering | Journal |
Volume | Issue | ISSN |
65 | 2 | 0018-9529 |
Citations | PageRank | References |
3 | 0.44 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Hu | 1 | 7 | 1.92 |
| Piero Baraldi | 2 | 236 | 21.96 |
| Francesco Di Maio | 3 | 124 | 14.20 |
| Enrico Zio | 4 | 77 | 7.43 |