Published December 2006
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Distributed Fault Diagnosis using Sensor Networks and Consensus-based Filters
Chicago
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.Attached Files
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Additional details
- Eprint ID
- 77114
- Resolver ID
- CaltechAUTHORS:20170501-174658779
- Ministero della Pubblica Istruzione, Università, Ricerca Scientifica e Tecnologica
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2017-05-03Created from EPrint's datestamp field
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2021-11-15Created from EPrint's last_modified field