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- Title
Dynamical Linear Models for Condition Monitoring with Multivariate Sensor Data.
- Authors
Vanem, Erik; Glad, Ingrid Kristine; Storvik, Geir Olve
- Abstract
This paper presents an application of dynamical linear models for anomaly detection & condition monitoring of ship machinery systems based on multivariate sensor data. Various model alternatives are specified and fitted to a set of training data before they are applied to a test set. Sequential modelling based on statistical tests are applied to detect model breakdown as an indication of deviation from normal conditions. The framework is very flexible and allows for a range of different candidate models to be specified. In this paper, some of the estimated models perform rather poorly, but the best ones did quite well in flagging anomalies in the data streams. Hence, it is demonstrated that the dynamical linear models may be utilized for anomaly detection and condition monitoring with multivariate sensor data. However, identification of the best model structure is challenging and requires representative training data and careful consideration in the model specification.
- Subjects
MONITORING of machinery; ANOMALY detection (Computer security); MARINE machinery
- Publication
International Journal of COMADEM, 2017, Vol 20, Issue 1, p64
- ISSN
1363-7681
- Publication type
Abstract