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A neural network to correct mass flow errors caused by two-phase flow in a digital coriolis mass flowmeter

Abstract:

Coriolis mass flow meters provide accurate measurement of single-phase flows, typically to 0.2%. However gas-liquid two-phase flow regimes may cause severe operating difficulties as well as measurement errors in these flow meters. As part of the Sensor Validation (SEVA) research at Oxford University a new fully digital coriolis transmitter has been developed which can operate with highly aerated fluids. This paper describes how a neural network has been used to correct the mass flow measureme...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/S0955-5986(00)00045-5

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
Publisher:
Elsevier Publisher's website
Journal:
Flow Measurement and Instrumentation
Volume:
12
Issue:
1
Pages:
53-63
Publication date:
2001-01-24
Acceptance date:
2000-09-07
DOI:
ISSN:
0955-5986
Keywords:
Pubs id:
pubs:64513
UUID:
uuid:5f3c7d55-e1f7-4154-8685-4534ad2a0653
Local pid:
pubs:64513
Deposit date:
2016-10-01

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