Publication detail

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

ŠŤASTNÝ, J. RICHTER, J. ŠŤASTNÝ, P.

Czech title

Puužití neuronových sítí pro určení vektoru rychlosti vzduchového proudu

English title

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

Type

journal article in Scopus

Language

en

Original abstract

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.

Czech abstract

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.

English abstract

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.

Keywords in English

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

RIV year

2014

Released

01.10.2014

Publisher

Mendel University in Brno

ISSN

1211-8516

Volume

62

Number

4

Pages from–to

757–768

Pages count

14

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",
  year="2014",
  volume="62",
  number="4",
  month="October",
  pages="757--768",
  publisher="Mendel University in Brno",
  issn="1211-8516"
}