Abstract
The main objective of this paper is to present a new method of detection and isolation with a Bayesian network. For that, a combination of two original works is made. The first one is the work of Li et al. [1] who proposed a causal decomposition of the T2 statistic. The second one is a previous work on the detection of fault with Bayesian networks [2], notably on the modeling of multivariate control charts in a Bayesian network. Thus, in the context of multivariate processes, we propose an original network structure allowing to decide if a fault has appeared in the process. This structure permits the isolation of the variables implicated in the fault. A particular interest of the method is the fact that the detection and the isolation can be made with a unique tool: a Bayesian network.
Original language | English (US) |
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Pages (from-to) | 902-911 |
Number of pages | 10 |
Journal | Journal of Process Control |
Volume | 20 |
Issue number | 8 |
DOIs | |
State | Published - Sep 2010 |
Keywords
- Bayesian network
- Multivariate SPC
- T decomposition
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Computer Science Applications
- Industrial and Manufacturing Engineering