Evaluation of thermography-based automated delamination and cavity detection in concrete bridges

Merkle, Dominik; Reiterer, Alexander

doi:10.1117/12.2592303

Cited by 3 publications

(3 citation statements)

References 12 publications

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“…To overcome this problem we performed tests using passive thermography. 20 Due to its dependency on the external temperature gradient, we developed an active system using a high-energy pulsed laser creating a plasma-induced shockwave on the concrete surface. 21 a preliminary design is depicted in Figure 3.…”

Section: Autonomous Lidar-based Cavity Detectionmentioning

confidence: 99%

Autonomous measurement robotics for advanced mapping and inspection tasks in complex environments

Merkle,

Villinger,

Gangelhoff

et al. 2024

Optical Sensing and Detection VIII

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Mapping the environment is the basis for measurement tasks, planning processes, monitoring over time, and decision-making. Moreover, the inspection of engineering structures, roads and railways, water and wastewater, and energy infrastructure is essential to ensure safety and sustainability. For an automated mapping and inspection process, the use of robotic systems is indispensable. Due to the complexity of the environments of structures and the requirements for inspection, the automated operation requires real-time navigation, specific sensor solutions, and automated interpretation of the data. In this study, we present various concepts of autonomous measurement robotics for mapping and inspecting challenging environments and damage types. Robotic systems based on unmanned aerial vehicles, unmanned ground vehicles, and unmanned underwater vehicles are addressed for various scenarios including pipes, dams, bridges, tunnels, coastal areas from the air, and underwater structures. After identifying the demands and needs and presenting the state-of-the-art methods and systems and their identifying limitations, we present ways for an autonomous operation of robotic systems equipped with specific sensors for LiDAR-based subsurface damage detection of cavities or delaminations, underwater laser scanning, high-resolution bathymetry, and multispectral LiDAR for moisture detection. This includes real-time data interpretation, iterative inspection strategies, automated data interpretation, and the strategy for the integration of the human operator. In conclusion, this work gives an overview of existing methods and systems and their limitations for mapping and inspection tasks. Moreover, we show how advanced sensor systems can be used as part of autonomous robotic systems to overcome current limitations for high-quality mapping and inspection of challenging environments and structures.

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Section: Autonomous Lidar-based Cavity Detectionmentioning

confidence: 99%

Autonomous measurement robotics for advanced mapping and inspection tasks in complex environments

Merkle,

Villinger,

Gangelhoff

et al. 2024

Optical Sensing and Detection VIII

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“…While the minimum detectable crack width is dependent on the sensor and image acquisition constraints, the measurement accuracy is dependent on the projection and mesh quality. For the localization of image information, photogrammetric approaches based on SfM can be used as proposed for thermal images (Merkle and Reiterer, 2021), visual damage inspection, or deformation analysis (Hallermann et al, 2018).…”

Section: The Current Situation Regarding Crack Detection and Localiza...mentioning

confidence: 99%

Semi-automatic 3D crack map generation and width evaluation for structural monitoring of reinforced concrete structures

Merkle,

Solass,

Schmitt

et al. 2023

ITcon

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Bridge inspection is a time-consuming, expensive, but indispensable task. In this work, a new semi-automatic workflow for a concrete bridge condition assessment system is developed and discussed. The workflow consists of three main parts merged in the new methodology. The elements are the data acquisition with cameras, the automated damage detection and localization using a neural network, and the resulting engineering condition assessment. Furthermore, a CAD model serves as a base for the later calculations for the condition assessment. Camera images are used for both sub-millimeter crack detection using semantic segmentation by an artificial neural network and a crack localization based on a combination of a photogrammetric workflow including structure from motion (SfM) and the projection as imprinted points directly onto the as-planned CAD mesh. Moreover, an approach for crack width derivation is given. The captured crack width, crack position, and the date of detection represent the input values for subsequent crack monitoring. Thereby, this new concept is proposed as an essential step towards a time-efficient and objective life-cycle assessment of reinforced concrete structures.

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“…Abgesehen von sichtbaren Schäden können z. B. Hohlstellen durch Thermalaufnahmen detektiert und dann in 3D über Fotogrammetrie [22] oder eine Kombination mit Laserscanning verortet werden. Thermalaufnahmen geben dabei die von der Kamera empfangene Infrarotstrahlung wieder, welche einen Rückschluss auf die Oberflächentemperatur zulässt.…”

Section: Anwendungsbeispiel Brückeunclassified

Digitalisierung von Bestandsbauwerken mit KI

2022

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Der Zustand eines Bauwerks ist dadurch gekennzeichnet, dass er sich mit zunehmendem Alter immer schneller verschlechtert. Eine vorbeugende Maßnahme gegen die Alterung ist umso erfolgreicher, je früher sie ergriffen wird. Um die Nutzung komplexer Bauwerke zu verlängern, sind umfassende Informationen zu einem möglichst frühen Zeitpunkt erforderlich. Auf dem Weg zu einer vorausschauenden Instandhaltung ist Grundlagenforschung zu den Methoden der Erfassung, Zusammenführung und Auswertung aller Geometrie‐, Material‐, Spannungs‐ und Alterungsdaten erforderlich. Die Digitalisierung im Sinne der Erzeugung eines Digitalen Zwillings erhält in diesem Zusammenhang eine völlig neue Bedeutung. Sie ermöglicht die Zusammenführung und Echtzeitauswertung aller für Betrieb und Instandhaltung erforderlichen Daten. Die Bauwirtschaft steht hier jedoch vor besonderen Herausforderungen. Bauwerke, insbesondere in der Verkehrsinfrastruktur, sind einzigartige Objekte. Sie zeichnen sich durch enorme Dimensionen aus und haben eine wesentlich längere Lebensdauer als andere technische Anlagen. Die Veränderungen im Sinne einer Zustandsverschlechterung sind sehr gering und daher kaum messbar. Die Basis eines umfassenden Zustandsmonitorings ist eine umfassende und komplette digitale Repräsentation des Bauwerks. Dies bedeutet eine Abbildung der kompletten äußeren und inneren Struktur in einer digitalen Form, inkl. Informationen zu Materialien, Schadstellen etc. Daraus lässt sich die Forschungsfrage ableiten, ob sich eine solche Abbildung effizient umsetzen lässt und in welcher Form und mit welchen Methoden dies möglich ist. Der vorliegende Beitrag gibt einen Überblick, wie die Umsetzung auch für komplexe Objekte gelingt und wie das generierte Modell mit semantischer Information angereichert werden kann.

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Evaluation of thermography-based automated delamination and cavity detection in concrete bridges

Cited by 3 publications

References 12 publications

Autonomous measurement robotics for advanced mapping and inspection tasks in complex environments

Autonomous measurement robotics for advanced mapping and inspection tasks in complex environments

Semi-automatic 3D crack map generation and width evaluation for structural monitoring of reinforced concrete structures

Digitalisierung von Bestandsbauwerken mit KI

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