A probabilistic model for information and sensor validation

Ibargüengoytia, PH, Vadera, S ORCID: https://orcid.org/0000-0001-6041-2646 and Sucar, LE 2006, 'A probabilistic model for information and sensor validation' , Computer Journal, 49 (1) , pp. 113-126.

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This paper develops a new theory and model for information and sensor validation. The model represents relationships between variables using Bayesian networks and utilizes probabilistic propagation to estimate the expected values of variables. If the estimated value of a variable differs from the actual value, an apparent fault is detected. The fault is only apparent since it may be that the estimated value is itself based on faulty data. The theory extends our understanding of when it is possible to isolate real faults from potential faults and supports the development of an algorithm that is capable of isolating real faults without deferring the problem to the use of expert provided domain-specific rules. To enable practical adoption for real-time processes, an any time version of the algorithm is developed, that, unlike most other algorithms, is capable of returning improving assessments of the validity of the sensors as it accumulates more evidence with time. The developed model is tested by applying it to the validation of temperature sensors during the start-up phase of a gas turbine when conditions are not stable; a problem that is known to be challenging. The paper concludes with a discussion of the practical applicability and scalability of the model.

Item Type: Article
Themes: Subjects / Themes > Q Science > QA Mathematics > QA075 Electronic computers. Computer science
Subjects / Themes > Q Science > QA Mathematics
Subjects outside of the University Themes
Schools: Schools > School of Computing, Science and Engineering
Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: Computer Journal
Publisher: Oxford University Press on behalf of The British Computer Society
Refereed: Yes
ISSN: 00104620
Depositing User: H Kenna
Date Deposited: 07 Jan 2009 14:35
Last Modified: 15 Feb 2022 15:33
URI: https://usir.salford.ac.uk/id/eprint/942

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