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Cooling tower measurement by laser scanner and close-range photogrammetry

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F23%3A00368539" target="_blank" >RIV/68407700:21110/23:00368539 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://doi.org/10.1063/5.0170899" target="_blank" >https://doi.org/10.1063/5.0170899</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1063/5.0170899" target="_blank" >10.1063/5.0170899</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Cooling tower measurement by laser scanner and close-range photogrammetry

  • Popis výsledku v původním jazyce

    Cooling towers with natural draft are mainly used in large power or chemical plants. The shape of cooling tower is rotation hyperboloid in order to gain optimal performance of natural draft. The height of cooling tower is designed by maximum cooling capacity. The smallest cooling tower has 35m (Heerlen – NL 1914) and the biggest tower reaches the height of 200m (Niederaussen – D 1998). Perfect geometry of rotation hyperboloid must be respected as a thin thickness of tower is susceptible to vibration and gusts of wind. This study offers a comparison of measured towers shape and model from blueprints. Data were obtained by laser scanning and close-range photogrammetry. During the measurement the cooling tower was inoperative, so it was possible to measure even inside the cooling tower. Model was processed in Reality Capture software which allows to combine laser scan and photogrammetry data. Final model was used for comparison with mathematical model of rotation hyperboloid, shell thickness analysis and damage detection of outer tower shell. Geometrical analyses processed in Cloud Compare software show the difference of reference model against tested model and the result is difference model. Mathematical model of rotation hyperboloid was represented by mesh, and it was created in Blender software. Texture of outer tower shell was projected by cylindrical formula to map for damage detection. Damages like crack and exposed reinforcement were visible on outer tower shell. Summarization of these damages allows determination cooling tower liveliness. Damage detection analysis was obtained by deep learning by CNN model and OBIA in eCognition software.

  • Název v anglickém jazyce

    Cooling tower measurement by laser scanner and close-range photogrammetry

  • Popis výsledku anglicky

    Cooling towers with natural draft are mainly used in large power or chemical plants. The shape of cooling tower is rotation hyperboloid in order to gain optimal performance of natural draft. The height of cooling tower is designed by maximum cooling capacity. The smallest cooling tower has 35m (Heerlen – NL 1914) and the biggest tower reaches the height of 200m (Niederaussen – D 1998). Perfect geometry of rotation hyperboloid must be respected as a thin thickness of tower is susceptible to vibration and gusts of wind. This study offers a comparison of measured towers shape and model from blueprints. Data were obtained by laser scanning and close-range photogrammetry. During the measurement the cooling tower was inoperative, so it was possible to measure even inside the cooling tower. Model was processed in Reality Capture software which allows to combine laser scan and photogrammetry data. Final model was used for comparison with mathematical model of rotation hyperboloid, shell thickness analysis and damage detection of outer tower shell. Geometrical analyses processed in Cloud Compare software show the difference of reference model against tested model and the result is difference model. Mathematical model of rotation hyperboloid was represented by mesh, and it was created in Blender software. Texture of outer tower shell was projected by cylindrical formula to map for damage detection. Damages like crack and exposed reinforcement were visible on outer tower shell. Summarization of these damages allows determination cooling tower liveliness. Damage detection analysis was obtained by deep learning by CNN model and OBIA in eCognition software.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    20101 - Civil engineering

Návaznosti výsledku

  • Projekt

  • Návaznosti

    S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2023

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    WORLD MULTIDISCIPLINARY CIVIL ENGINEERING-ARCHITECTURE-URBAN PLANNING SYMPOSIUM WMCAUS 2022

  • ISBN

  • ISSN

    0094-243X

  • e-ISSN

    1551-7616

  • Počet stran výsledku

    10

  • Strana od-do

  • Název nakladatele

    AIP Conference Proceedings

  • Místo vydání

    New York

  • Místo konání akce

    Praha

  • Datum konání akce

    5. 9. 2022

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku