Journal article
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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Authors
Bibliographic Details
- Publisher:
- Elsevier Publisher's website
- Journal:
- Flow Measurement and Instrumentation
- Volume:
- 12
- Issue:
- 1
- Pages:
- 53-63
- Publication date:
- 2001-03-01
- Acceptance date:
- 2000-09-07
- DOI:
- EISSN:
-
1873-6998
- ISSN:
-
0955-5986
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
pubs:64513
- UUID:
-
uuid:77d33cb9-79fc-45b2-b0e0-9c955173dfd3
- Local pid:
- pubs:64513
- Source identifiers:
-
64513
- Deposit date:
- 2013-11-16
Terms of use
- Copyright holder:
- Elsevier Science Ltd
- Copyright date:
- 2001
- Notes:
-
This is an
accepted manuscript of a journal article published by Elsevier in Flow Measurement and Instrumentation on 2001-01-24, available online: http://dx.doi.org/10.1016/S0955-5986(00)00045-5
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