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ANN based modeling, testing and diagnosis of MEMS

Record type: Conference or Workshop Item (Paper)

New concepts of simulation, testing and diagnosis of MEMS are proposed, intended to boost the time to market and dependability of such systems. Black-box modeling of non-electronic parts is introduced using artificial neural networks, so enabling radically faster simulation without concurrent algorithms and parallel computation. A Jumped model of the capacitive transducer, being the part of a micro-electro-mechanical capacitive pressure sensing system, is created using an ANN. Faults are then introduced to the sensing system and simulation of the fault-free and faulty circuits are demonstrated.

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Citation

Litovski, V, Andrejevic, M and Zwolinski, M (2004) ANN based modeling, testing and diagnosis of MEMS At NEUREL 2004: SEVENTH SEMINAR ON NEURAL NETWORK APPLICATIONS IN ELECTRICAL ENGINEERING, Serbia. 23 - 25 Sep 2004. , pp. 183-188.

More information

Published date: 2004
Additional Information: Event Dates: SEP 23-25, 2004
Venue - Dates: NEUREL 2004: SEVENTH SEMINAR ON NEURAL NETWORK APPLICATIONS IN ELECTRICAL ENGINEERING, Serbia, 2004-09-23 - 2004-09-25
Organisations: EEE

Identifiers

Local EPrints ID: 263413
URI: http://eprints.soton.ac.uk/id/eprint/263413
ISBN: 0-7803-8547-0
PURE UUID: 60e81b49-bed7-4c07-bbea-df19722a56d7
ORCID for M Zwolinski: ORCID iD orcid.org/0000-0002-2230-625X

Catalogue record

Date deposited: 12 Feb 2007
Last modified: 18 Jul 2017 07:45

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Contributors

Author: V Litovski
Author: M Andrejevic
Author: M Zwolinski ORCID iD

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