Automation of data processing obtained by IPI method

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F18%3A00326170" target="_blank" >RIV/68407700:21220/18:00326170 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Automation of data processing obtained by IPI method

Popis výsledku v původním jazyce

The paper describes an approach for automation of image processing obtained by IPI (Interferometric Particle Imaging), or also called ILIDS (Interferometric Laser Imaging for Droplet Size), method, which is used for measurement of spherical and transparent particle size. If the test section is relatively large and daylight can’t be fully eliminated, signal noise is present in the measured data and conventional approaches used in the past can not be applied for automatic data evaluation. In this work is proposed an algorithm of interferogram detection based on cross-correlation, thresholding and Hough transform. The detection is then checked by region based convolutional neural network. The algorithm is programmed in Matlab and ImageJ (MIJ) and it is tested on data acquired during measurement of eliminator efficiency in a cooling tower.

Název v anglickém jazyce

Automation of data processing obtained by IPI method

Popis výsledku anglicky

The paper describes an approach for automation of image processing obtained by IPI (Interferometric Particle Imaging), or also called ILIDS (Interferometric Laser Imaging for Droplet Size), method, which is used for measurement of spherical and transparent particle size. If the test section is relatively large and daylight can’t be fully eliminated, signal noise is present in the measured data and conventional approaches used in the past can not be applied for automatic data evaluation. In this work is proposed an algorithm of interferogram detection based on cross-correlation, thresholding and Hough transform. The detection is then checked by region based convolutional neural network. The algorithm is programmed in Matlab and ImageJ (MIJ) and it is tested on data acquired during measurement of eliminator efficiency in a cooling tower.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20302 - Applied mechanics

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Studentská tvůrčí činnost 2018

ISBN

978-80-01-06421-4

ISSN

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e-ISSN

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Počet stran výsledku

4

Strana od-do

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Název nakladatele

České vysoké učení technické v Praze, Fakulta strojní

Místo vydání

Praha

Místo konání akce

Praha

Datum konání akce

11. 4. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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