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Article . 1992 . Peer-reviewed
Full-Text: https://eprints.soton.ac.uk/253900/1/COMPELvol11y1992page69.pdf
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COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
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COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
Article . 1992 . Peer-reviewed
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https://dx.doi.org/10.1108/eb0...
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FINITE ELEMENT MODELLING OF INDUCTIVE SENSORS

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 1992 United Kingdom English Publisher:EmeraldJournal:COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, volume 11, pages 69-72 (issn: 0332-1649, Copyright policy )
Authors: Sykulski, J.K.; Stoll, R.L.;

doi: 10.1108/eb051754

FINITE ELEMENT MODELLING OF INDUCTIVE SENSORS

Abstract

Practical aspects of finite‐element modelling of magnetic fields and calculating integral parameters such as a reflected impedance in inductive sensing devices are discussed. The electromagnetics of such sensors is briefly explained and some practical modelling techniques are put forward. Excellent agreement with experiment is reported.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Top 10%
Average
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