Detail publikačního výsledku

Using Neural Networks for Determining Velocity Vectors of Air Flow Visualized by Helium Bubbles

ŠŤASTNÝ, J.; RICHTER, J.; ŠŤASTNÝ, P.

Originální název

Using Neural Networks for Determining Velocity Vectors of Air Flow Visualized by Helium Bubbles

Anglický název

Using Neural Networks for Determining Velocity Vectors of Air Flow Visualized by Helium Bubbles

Druh

Článek Scopus

Originální abstrakt

One of the important characteristics of air flow is the velocity of flow. To determine the speed, in addition to other methods, we also use the helium bubbles seeding visualization method, when bubbles are injected into the air stream so that the air flow is obvious to the eye. If a video of such flow is taken, it is possible to determine velocity vectors in a pair of consecutive frames of this video footage, derived from the change in position of individual bubbles. This article describes a method of monitoring the bubbles in consecutive video frames. During this process, helium bubbles are detected in the first image of the pair, either by a firmly defined procedure, or with the use of a neural network. For detected bubbles, the velocity vectors are determined according to the way in which they move, therefore, according to their location in the following frame. Another neural network then determines the velocity vector at any point of image, which will be implemented in the construction of vector maps for the first image. A vector map is used for comprehensive evaluation of air flow and thus, plays an important role in the development of ventilation and air conditioning systems.

Anglický abstrakt

One of the important characteristics of air flow is the velocity of flow. To determine the speed, in addition to other methods, we also use the helium bubbles seeding visualization method, when bubbles are injected into the air stream so that the air flow is obvious to the eye. If a video of such flow is taken, it is possible to determine velocity vectors in a pair of consecutive frames of this video footage, derived from the change in position of individual bubbles. This article describes a method of monitoring the bubbles in consecutive video frames. During this process, helium bubbles are detected in the first image of the pair, either by a firmly defined procedure, or with the use of a neural network. For detected bubbles, the velocity vectors are determined according to the way in which they move, therefore, according to their location in the following frame. Another neural network then determines the velocity vector at any point of image, which will be implemented in the construction of vector maps for the first image. A vector map is used for comprehensive evaluation of air flow and thus, plays an important role in the development of ventilation and air conditioning systems.

Klíčová slova

Helium bubbles seeding, air jet velocity, Multilayer Perceptron Neural Network, recognition, vector approximation

Klíčová slova v angličtině

Helium bubbles seeding, air jet velocity, Multilayer Perceptron Neural Network, recognition, vector approximation

Autoři

ŠŤASTNÝ, J.; RICHTER, J.; ŠŤASTNÝ, P.

Rok RIV

2015

Vydáno

01.10.2014

Nakladatel

Mendel University in Brno

ISSN

1211-8516

Periodikum

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis

Svazek

62

Číslo

4

Stát

Česká republika

Strany od

757

Strany do

768

Strany počet

14

URL

Plný text v Digitální knihovně

BibTex

@article{BUT110144,
  author="Jiří {Šťastný} and Jan {Richter} and Petr {Šťastný}",
  title="Using Neural Networks for Determining Velocity Vectors of Air Flow Visualized by Helium Bubbles",
  journal="Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis",
  year="2014",
  volume="62",
  number="4",
  pages="757--768",
  doi="10.11118/actaun201462040757",
  issn="1211-8516",
  url="http://acta.mendelu.cz/artkey/acu-201404-0016_using-neural-networks-for-determining-velocity-vectors-of-air-flow-visualized-by-helium-bubbles.php"
}

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