Intelligent fuel-flow monitoring based on particle-tracking velocimetry

Artificial neural-networks have been widely applied in various aspects of particle-tracking velocimetry. This paper presents an overview of the different applications and gives an insight into how this technology can be applied to fuel-flow monitoring. The paper presents a method of flow-field estim...

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Bibliographic Details
Published inIET Seminar on Target Tracking and Data Fusion: Algorithms and Applications pp. 215 - 221
Main Authors Ingram, S, Hossain, M.A, Dahl, K.P
Format Conference Proceeding
LanguageEnglish
Published Stevenage IET 2008
Subjects
Aerospace control
Level, flow and volume control
Neurocontrol
intelligent fuel-flow monitoring
particle-tracking velocimetry
neurocontrollers
artificial neural-networks
fuel systems
computerised monitoring
optical velocimetry
avionics
flow control
light velocity measurement
particle velocity analysis
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ISBN0863419100
9780863419102
DOI10.1049/ic:20080074

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Summary:Artificial neural-networks have been widely applied in various aspects of particle-tracking velocimetry. This paper presents an overview of the different applications and gives an insight into how this technology can be applied to fuel-flow monitoring. The paper presents a method of flow-field estimation based on particle-tracking velocimetry, without the need to solve the correspondence problem. We also present a method of defeating the obscuration problem found in many optical velocimetry schemes.
ISBN:0863419100
9780863419102
DOI:10.1049/ic:20080074