In the present paper we address the problem of computing the Minimal Sensor Sets that guarantee a desired level of diagnostic discrimination for a system. Unlike other approaches previously proposed in the literature, we compute MSSs starting from precompiled discriminability relations that are parsimoniously stored using a symbolic representation. Such discriminability relations are built from an extended model of the system to be diagnosed which includes a set of switches modeling the inclusion (or the exclusion) of potentially observable variables into the set of actual observations. The main advantage of the approach is that the precompiled relations can be reused for efficiently computing MSSs under different discriminability requirements and constraints on the selection of measurement points. This possibility can be exploited for conveniently analyzing different scenarios at design time, as well as for reacting to changes in requirements and constraints that happen after the MSSs have been computed. Encouraging experimental results collected from the application of the proposed solution to the model of a non-trivial combinatorial digital circuit are reported.

Computation of Minimal Sensor Sets from Precompiled Discriminability Relations

TORTA, GIANLUCA;TORASSO, Pietro
2007

Abstract

In the present paper we address the problem of computing the Minimal Sensor Sets that guarantee a desired level of diagnostic discrimination for a system. Unlike other approaches previously proposed in the literature, we compute MSSs starting from precompiled discriminability relations that are parsimoniously stored using a symbolic representation. Such discriminability relations are built from an extended model of the system to be diagnosed which includes a set of switches modeling the inclusion (or the exclusion) of potentially observable variables into the set of actual observations. The main advantage of the approach is that the precompiled relations can be reused for efficiently computing MSSs under different discriminability requirements and constraints on the selection of measurement points. This possibility can be exploited for conveniently analyzing different scenarios at design time, as well as for reacting to changes in requirements and constraints that happen after the MSSs have been computed. Encouraging experimental results collected from the application of the proposed solution to the model of a non-trivial combinatorial digital circuit are reported.
18th Workshop on Principle of Diagnosis (DX 07)
Nashville, TN, USA
29-31/5/2007
Proc. 18th Workshop on Principle of Diagnosis (DX 07)
Vanderbilt University
202
209
http://w3.isis.vanderbilt.edu/dx07/
Sensor Placement; diagnosis; knowledge compilation
G. TORTA; P. TORASSO
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/28726
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