Sensor fault diagnosis using Bayesian belief networks
Journal Article
·
· Transactions of the American Nuclear Society
OSTI ID:552402
- Univ. of New Mexico, Albuquerque, NM (United States)
This paper describes a method based on Bayesian belief networks (BBNs) sensor fault detection, isolation, classification, and accommodation (SFDIA). For this purpose, a BBN uses three basic types of nodes to represent the information associated with each sensor: (1) sensor-reading nodes that represent the mechanisms by which the information is communicated to the BBN, (2) sensor-status nodes that convey the status of the corresponding sensors at any given time, and (3) process-variable nodes that are a conceptual representation of the actual values of the process variables, which are unknown.
- OSTI ID:
- 552402
- Report Number(s):
- CONF-971125--
- Journal Information:
- Transactions of the American Nuclear Society, Journal Name: Transactions of the American Nuclear Society Vol. 77; ISSN 0003-018X; ISSN TANSAO
- Country of Publication:
- United States
- Language:
- English
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