A Structural Approach to Sensor Placement based on Symbolic Compilation of the Model

: In the present paper we address the problem of computing the Minimal Additional Sensor Sets (MASS) that guarantee a desired level of diagnostic discrimination for a system. Recently, techniques based on the symbolic compilation of qualitative system models have been proposed for the computation of MASS. The main contribution of this paper is the adaptation and application of such techniques to a structural approach suitable for the computation of MASS for component-oriented models consisting of sets of numerical equations. In this respect, the paper can be viewed as a bridge across the AI and FDI approaches to model-based sensor placement. In particular, our approach derives the MASS for a given system starting from a Resolution Process Graph which associates a subset of equations to the set of unknown variables and defines the set of redundant relations. We show that the resulting method exploits the symbolic compilation techniques not only as a way to provide computational savings ...

• Type: Journal
• Year: 2010
• Where: SGAI
• Authors: Gianluca Torta, Pietro Torasso
• Keywords: Artificial Intelligence, Mass, Minimal Additional Sensor, SGAI 2010, Symbolic Compilation