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Behavioural Modelling, Simulation, Test and Diagnosis of MEMS using ANNs

Record type: Conference or Workshop Item (Paper)

The design of Micro-Electrical-Mechanical Systems requires that the entire system can be modelled and simulated. Additionally, behaviour under fault conditions must be simulated to determine test and diagnosis strategies. While the electrical parts of a system can be modelled at transistor, gate or behavioural levels, the mechanical parts are conventionally modelled in terms of partial differential equations (PDEs). Mixed-signal electrical simulations are possible, using e.g. VHDL-AMS, but simulations that include PDEs are prohibitively expensive. Here, we show that complex PDEs can be replaced by black-box functional models and, importantly, such models can be characterized automatically and rapidly using artificial neural networks (ANNs). We demonstrate a significant increase in simulation speed and show that test and diagnosis strategies can be derived using such models.

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Citation

Litovski, V, Andrejević, M and Zwolinski, M (2005) Behavioural Modelling, Simulation, Test and Diagnosis of MEMS using ANNs At International Symposium on Circuits and Systems, Japan. 23 - 26 May 2005.

More information

Published date: 2005
Additional Information: Event Dates: 23-26 May 2005
Venue - Dates: International Symposium on Circuits and Systems, Japan, 2005-05-23 - 2005-05-26
Organisations: EEE

Identifiers

Local EPrints ID: 260432
URI: http://eprints.soton.ac.uk/id/eprint/260432
PURE UUID: bbe75f50-0710-461c-befc-3fdc7902882f
ORCID for M Zwolinski: ORCID iD orcid.org/0000-0002-2230-625X

Catalogue record

Date deposited: 03 Feb 2005
Last modified: 18 Jul 2017 09:13

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Contributors

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

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