Volume 10, Issue 1, 2017, Pages 176 - 195
An Application of Dynamic Bayesian Networks to Condition Monitoring and Fault Prediction in a Sensored System: a Case Study
Authors
Javier Cózar1, javier.cozar@uclm.es, José M. Puerta1, jose.puerta@uclm.es, José A. Gámez1, jose.gamez@uclm.es
Received 8 June 2016, Accepted 24 September 2016, Available Online 1 January 2017.
- DOI
- 10.2991/ijcis.2017.10.1.13How to use a DOI?
- Keywords
- Bayesian networks; anomaly detection; sensor networks; predictive maintenance; condition monitoring
- Abstract
Bayesian networks have been widely used for classification problems. These models, structure of the network and/or its parameters (probability distributions), are usually built from a data set. Sometimes we do not have information about all the possible values of the class variable, e.g. data about a reactor failure in a nuclear power station. This problem is usually focused as an anomaly detection problem. Based on this idea, we have designed a decision support system tool of general purpose.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - Javier Cózar AU - José M. Puerta AU - José A. Gámez PY - 2017 DA - 2017/01/01 TI - An Application of Dynamic Bayesian Networks to Condition Monitoring and Fault Prediction in a Sensored System: a Case Study JO - International Journal of Computational Intelligence Systems SP - 176 EP - 195 VL - 10 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.2017.10.1.13 DO - 10.2991/ijcis.2017.10.1.13 ID - Cózar2017 ER -