Integration of Measurement Data into Probability Assessment of High-voltage Assets
Abstract
Knowing the failure probability of high-voltage assets becomes increasingly important. Measurement data gives an indication of the failure probability, which is manly based on threshold values for these measurements. Values below the threshold are not considered at all or by a warning range shortly before reaching the threshold value. The presented work introduces a methodology to quantify the failure probability depending on the difference between the measured and threshold value. Therefore, Bayes’ theorem is used to assess the failure probability, while measurement data determines the conditional probability through a shift of the probability density function of the measured data. The methodology is exemplified by gas density measurements of circuit breakers.
Details
- Organisationseinheit(en)
-
Fachgebiet Hochspannungstechnik und Asset Management (Schering-Institut)
- Externe Organisation(en)
-
Tennet TSO GmbH
Institut für integrierte Produktion Hannover (IPH) gGmbH
- Typ
- Aufsatz in Konferenzband
- Band
- 2023
- Seiten
- 997-1003
- Anzahl der Seiten
- 7
- Publikationsdatum
- 28.08.2023
- Publikationsstatus
- Veröffentlicht
- Peer-reviewed
- Ja
- ASJC Scopus Sachgebiete
- Allgemeiner Maschinenbau
- Elektronische Version(en)
-
https://doi.org/10.1049/icp.2024.0738 (Zugang:
Geschlossen
)
