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Published December 2006 | Published
Book Section - Chapter Open

Distributed Fault Diagnosis using Sensor Networks and Consensus-based Filters

Abstract

This paper considers the problem of designing distributed fault diagnosis algorithms for dynamic systems using sensor networks. A network of distributed estimation agents is designed where a bank of local Kalman filters is embedded into each sensor. The diagnosis decision is performed by a distributed hypothesis testing method that relies on a belief consensus algorithm. Under certain assumptions, both the distributed estimation and the diagnosis algorithms are derived from their centralized counterparts thanks to dynamic average-consensus techniques. Simulation results are provided to demonstrate the effectiveness of the proposed architecture and algorithm.

Additional Information

© 2006 IEEE. This work has been partially supported by the Italian Ministry for University and Research.

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