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 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.