Linear smoothing of FRF for aicraft engine vibration monitoring
Overview & Synopsis
The problem of aircraft engine condition monitoring based on vibration signals is addressed. To do so, we compare two estimators of the Frequency Response Function of an aircraft engine which input is its shaft angular position and which output is an accelerometric signal that measures vibrations. It is shown that this problem can be seen as a smoothing problem, and that linear kernel smoothing such as Gaussian Process Regression allows the computation of the FRF
Indexed from repository: HAL Open Science
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hal.science)
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Document Information
| Document Title | Linear smoothing of FRF for aicraft engine vibration monitoring |
|---|---|
| Author / Organization | Aurélien Hazan, Michel Verleysen, Marie Cottrell, Jérôme Lacaille |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2010 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-45529 |
| Original Source Link | Visit Source Page on hal.science » |