Name
Title | ||
|---|---|---|
A possibilistic approach for measurement uncertainty propagation in prognostics and health management |
Abstract | ||
|---|---|---|
In this paper, a similarity-based data-driven prognostic algorithm for the estimation of the Remaining Useful Life of a product is proposed. It is based on the exploitation of run-to-failure data of products, which are supposed to be characterized by similar operational conditions. The core of the contribution is the application of a possibilistic framework, namely a Random-Fuzzy Variable approach, for the representation and propagation of the measurement uncertainty, which is a crucial source of uncertainty in Prognostics and Health Management. The results obtained for a real application case as Medium and High Voltage Circuit Breakers, have shown a high prognostic power of the algorithm, which therefore represents a potential tool for an effective Predictive Maintenance strategy. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/i2mtc.2018.8409739 | instrumentation and measurement technology conference |
Field | DocType | Citations |
Prognostics,Measurement uncertainty,Control engineering,Circuit breaker,Atmospheric measurements,Engineering,Predictive maintenance,High voltage | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Loredana Cristaldi | 1 | 45 | 14.08 |
| A. Ferrero | 2 | 376 | 88.12 |
| Giacomo Leone | 3 | 0 | 0.68 |
| Simona Salicone | 4 | 263 | 33.62 |