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A Framework for Self-Diagnosis and Condition Monitoring for Embedded Systems Using a SOM-Based Classifier

Sartain, P and Hopkins, ABT and McDonald-Mair, KD and Howells, WGJ (2008) A Framework for Self-Diagnosis and Condition Monitoring for Embedded Systems Using a SOM-Based Classifier. In: 2008 NASA/ESA Conference on Adaptive Hardware and Systems (AHS), 2008-06-22 - 2008-06-25.

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Abstract

This paper presents a system level framework for System-on-Chip (SoC) based embedded devices that may include adaptive and reconfigurable elements. Current development support and debugging solutions are highly dependant on off-line post-mortem style inspection, and even those that utilise tracing for real-time and schedule-critical systems rely on external development tools and environments. This new framework introduces an AI-lead infrastructure that has the potential to reduce much of the development effort while complementing existing debugging circuits. Specifically this paper investigates how to use a Kohonen self-organising map (SOM) as a classifier, and shows a preliminary investigation into how to determine the quality of a map after training. This classifier is a first step in diagnosing failure, degradation and anomalies (i.e. provides condition monitoring) in an embedded system from a system level point of view, and in the larger task of self-diagnosis of an embedded system. © 2008 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings of the 2008 NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2008
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 19 Sep 2013 09:33
Last Modified: 15 Jan 2022 00:32
URI: http://repository.essex.ac.uk/id/eprint/6888

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