Augmented Reality for Next Generation Infrastructure Inspections

Ballor, JoAnn P.; McClain, Oscar L.; Mellor, Miranda A.; Cattaneo, Alessandro; Harden, Troy; Shelton, Philo; Martínez, Eric J. Alfaro; Narushof, Ben; Moreu, Fernando; Mascareñas, David

doi:10.1007/978-3-319-74793-4_23

Cited by 11 publications

(8 citation statements)

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“…(Morales Garcia et al, 2017) used a similar approach with the HoloLens glasses for smart infrastructure inspection specifically with regards to the integration of thermal images (Morales Garcia et al, 2017). Continuing the work of Morales et al 2017and Ballor et al (2019) integrated measurement capabilities to the AR environment as they are a standard of visual inspections (Ballor et al, 2019). While these approaches mitigate the underlying issues of depicting complex geometries or intuitive on site viewing, they either still require a 3D model to built or do not address off site viewing capabilities.…”

Section: Review Of Current Methodologies and Existing Gapsmentioning

confidence: 99%

Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology

Napolitano

Liu

Sun

et al. 2019

Front. Built Environ.

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With the current deterioration rate of existing infrastructure, the importance of intervention and preservation efforts such as on-site visual inspections, non-destructive evaluation, structural health monitoring (SHM), and building pathology are on the rise. A critical aspect of these intervention and preservation methods is the visualization and accessibility of large, heterogeneous data sets. To enable diverse stakeholders to make informed choices, data and metadata for the built environment needs to be directly integrated into a user's viewing environment. To address this challenge, a human-machine interface which organizes these types of data and provides actionable information is necessary. The main aim of this work is to develop a preliminary framework for documenting and visualizing data about the built environment both on and off site using a combination of image-based documentation and augmented reality (AR). While this work illustrates preliminary annotation mechanisms such as drawing, the concept of projecting data between the image-based environment and the AR environment is the main contribution of this work. This method was applied to test objects as well as case studies in SHM and building pathology.

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Section: Review Of Current Methodologies and Existing Gapsmentioning

confidence: 99%

Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology

Napolitano

Liu

Sun

et al. 2019

Front. Built Environ.

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“…Behzadan et al 61 proposed a so-called line segment detector algorithm for automatic edge extraction and also a new computational framework for automated damage detection using AR. Ballor et al 62 developed several measurement and data storage apps which they deployed on the Microsoft HoloLens to enable infrastructure inspections.…”

Section: The Paradigm Of Enhanced Visual Inspection Using Armentioning

confidence: 99%

Augmented reality for enhanced visual inspection through knowledge-based deep learning

Wang

Zargar

Fang

2020

Structural Health Monitoring

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A two-stage knowledge-based deep learning algorithm is presented for enabling automated damage detection in real-time using the augmented reality smart glasses. The first stage of the algorithm entails the identification of damage prone zones within the region of interest. This requires domain knowledge about the damage as well as the structure being inspected. In the second stage, automated damage detection is performed independently within each of the identified zones starting with the one that is the most damage prone. For real-time visual inspection enhancement using the augmented reality smart glasses, this two-stage approach not only ensures computational feasibility and efficiency but also significantly improves the probability of detection when dealing with structures with complex geometric features. A pilot study is conducted using hands-free Epson BT-300 smart glasses during which two distinct tasks are performed: First, using a single deep learning model deployed on the augmented reality smart glasses, automatic detection and classification of corrosion/fatigue, which is the most common cause of failure in high-strength materials, is performed. Then, in order to highlight the efficacy of the proposed two-stage approach, the more challenging task of defect detection in a multi-joint bolted region is addressed. The pilot study is conducted without any artificial control of external conditions like acquisition angles, lighting, and so on. While automating the visual inspection process is not a new concept for large-scale structures, in most cases, assessment of the collected data is performed offline. The algorithms/techniques used therein cannot be implemented directly on computationally limited devices such as the hands-free augmented reality glasses which could then be used by inspectors in the field for real-time assistance. The proposed approach serves to overcome this bottleneck.

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“…Ballor et al investigated using AR in infrastructure inspections. The framework uses the headset's sensors to capture a high-resolution 3D measurement of the infrastructure which can be used to analyze the state of the structure over time, and track damage progression [13]. Researchers at Los Alamos National Laboratory used AR for structural health monitoring including detecting heat emitted from electronic equipment [14].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Human Cognition of Nearby Vibrations Using Augmented Reality

Wyckoff¹,

Ball²,

Moreu³

2021

Conference Proceedings of the Society for Experimental Mechanics Series

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Human-computer interaction is an important part of structural monitoring and the research community is interested in amplifying human cognition of structural response. Augmenting feedback closes the loop between reality and human, where normally the human would need to check a computer or other separate screen for information on the real-time structural response. The research proposes using an Augmented Reality (AR) application to provide inspectors with realtime information about structural responses, to allow the user to perceive real-time changes. The proposed research seeks to validate the AR application as a useful tool in the field. This paper presents the results of an experiment that show how AR can provide a channel for direct sensor feedback. The application displays a live graph of accelerometer data with a low delay close to real time. The results of the reported experiment prove the usefulness of the AR application in the field by comparing feedback delay over a local area network versus a mobile WiFi hotspot.

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Augmented Reality for Next Generation Infrastructure Inspections

Cited by 11 publications

References 0 publications

Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology

Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology

Augmented reality for enhanced visual inspection through knowledge-based deep learning

Real-Time Human Cognition of Nearby Vibrations Using Augmented Reality

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