Application of particle filtering for prognostics with measurement uncertainty in nuclear power plants - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Nuclear Engineering and Technology Année : 2018

Application of particle filtering for prognostics with measurement uncertainty in nuclear power plants

Résumé

For nuclear power plants (NPPs) to have long lifetimes, ageing is a major issue. Currently, ageing management for NPP systems is based on correlations built from generic experimental data. However, each system has its own characteristics, operational history, and environment. To account for this, it is possible to resort to prognostics that predicts the future state and time to failure (TTF) of the target system by updating the generic correlation with specific information of the target system. In this paper, we present an application of particle filtering for the prediction of degradation in steam generator tubes. With a case study, we also show how the prediction results vary depending on the uncertainty of the measurement data.
Fichier principal
Vignette du fichier
1-s2.0-S1738573318302742-main.pdf (1.84 Mo) Télécharger le fichier
Origine Publication financée par une institution
Loading...

Dates et versions

hal-01988934 , version 1 (22-01-2019)

Identifiants

Citer

Gibeom Kim, Hyeonmin Kim, Enrico Zio, Gyunyoung Heo. Application of particle filtering for prognostics with measurement uncertainty in nuclear power plants. Nuclear Engineering and Technology, 2018, 50 (8), pp.1314-1323. ⟨10.1016/j.net.2018.08.002⟩. ⟨hal-01988934⟩
56 Consultations
55 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More