Setting the Flight Parameters of an Unmanned Aircraft for Distress Detection on the Concrete Runway

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F26%3A00557207" target="_blank" >RIV/60162694:G43__/26:00557207 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9502737" target="_blank" >http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9502737</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICMT52455.2021.9502831" target="_blank" >10.1109/ICMT52455.2021.9502831</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Setting the Flight Parameters of an Unmanned Aircraft for Distress Detection on the Concrete Runway

Popis výsledku v původním jazyce

The airport pavement is annually inspected by a visual survey for the presence of distress to keep a high level of safe air traffic. The basic airport pavement distress is a crack, whose main criterion for evaluation is its width. In relation to air traffic safety, the cracks are divided into small, medium, or large categories according to the severity. A modern way of conduction of airport pavement inspection is the use of unmanned aircraft. This article explores the effect of unmanned aircraft flight parameter settings to recognize the distress on the concrete runway. The image data were obtained from the flights at several altitudes above the runway of a former military airport and processed using commercial multi-view reconstruction software. The output orthomosaic images were evaluated according to pixel resolution, ground sampling distance, and ground resolved distance. The correlation between the variables was statistically analyzed using linear and polynomial regression. The low flight altitudes bring a higher level of captured detail, but only the small area is captured, and more data needs to be processed, whereas higher flight altitudes cover a larger area with less data, but the captured detail is getting low. The findings reveal in order to capture the required detail; it is necessary to divide the length of the runway into individual legs, which allows the flight in lower altitudes above ground level. For the used unmanned aircraft, a balance between the flight altitude and the captured detail corresponding to the flight time per battery has been found. The captured data will be further used to create a database of individual distress for deep learning.

Název v anglickém jazyce

Setting the Flight Parameters of an Unmanned Aircraft for Distress Detection on the Concrete Runway

Popis výsledku anglicky

The airport pavement is annually inspected by a visual survey for the presence of distress to keep a high level of safe air traffic. The basic airport pavement distress is a crack, whose main criterion for evaluation is its width. In relation to air traffic safety, the cracks are divided into small, medium, or large categories according to the severity. A modern way of conduction of airport pavement inspection is the use of unmanned aircraft. This article explores the effect of unmanned aircraft flight parameter settings to recognize the distress on the concrete runway. The image data were obtained from the flights at several altitudes above the runway of a former military airport and processed using commercial multi-view reconstruction software. The output orthomosaic images were evaluated according to pixel resolution, ground sampling distance, and ground resolved distance. The correlation between the variables was statistically analyzed using linear and polynomial regression. The low flight altitudes bring a higher level of captured detail, but only the small area is captured, and more data needs to be processed, whereas higher flight altitudes cover a larger area with less data, but the captured detail is getting low. The findings reveal in order to capture the required detail; it is necessary to divide the length of the runway into individual legs, which allows the flight in lower altitudes above ground level. For the used unmanned aircraft, a balance between the flight altitude and the captured detail corresponding to the flight time per battery has been found. The captured data will be further used to create a database of individual distress for deep learning.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20304 - Aerospace engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

2021 8th International Conference on Military Technologies, ICMT 2021 - Proceedings

ISBN

978-1-6654-3724-0

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

320-327

Název nakladatele

Institute of Electrical and Electronics Engineers Inc.

Místo vydání

Brno

Místo konání akce

Brno, the Czech Republic

Datum konání akce

8. 6. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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