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"
}