Structural Health Monitoring of a Foot Bridge in Virtual Reality Environment

Luleci, Furkan; Li, Liangding; Chi, Jiapeng; Reiners, Dirk; Cruz-Neira, Carolina; Çatbaş, F. Necati

doi:10.1016/j.prostr.2022.01.060

Cited by 18 publications

(8 citation statements)

References 9 publications

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“…Luleci et al [ 12 ] addressed the challenge of site visits and inspections during the SHM procedure, which can be timely, costly, and risky. The authors proposed an approach where a civil structure (footbridge) and its operational SHM data are fused in a collaborative VR environment.…”

Section: Extended Reality For Structural Condition Assessment Of Civi...mentioning

confidence: 99%

“… ( a ) FEA reflected TLS point cloud with serviceability limit state check warning and dynamic monitoring of the midspan; ( b ) configuration panel of the FEA reflected TLS point cloud in immersive view; ( c ) dynamic monitoring of the all nodes with VR controller in immersive view; ( d , e ) multi-user feature; ( f ) iPad screen—iPad LiDAR footbridge scanning; ( g , h ) iPad LiDAR real-time footbridge reconstructing in the VR environment [ 12 ]. …”

Section: Figurementioning

confidence: 99%

“…One of the earliest machine-learning-based studies was conducted for SHM applications [ 8 , 9 ]. Furthermore, various other new implementations followed, such as using Mixed Reality (MR) to assist the inspectors on the field [ 10 , 11 ] and using Virtual Reality (VR) to bring the field data to the office where parties can collaborate in a single VR environment [ 12 ]. Another recent collaborative work discusses the latest trends in bridge health monitoring [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

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Extended Reality (XR) for Condition Assessment of Civil Engineering Structures: A Literature Review

Çatbaş

Luleci

Zakaria

et al. 2022

Sensors

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Condition assessment of civil engineering structures has been an active research area due to growing concerns over the safety of aged as well as new civil structures. Utilization of emerging immersive visualization technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) in the architectural, engineering, and construction (AEC) industry has demonstrated that these visualization tools can be paradigm-shifting. Extended Reality (XR), an umbrella term for VR, AR, and MR technologies, has found many diverse use cases in the AEC industry. Despite this exciting trend, there is no review study on the usage of XR technologies for the condition assessment of civil structures. Thus, the present paper aims to fill this gap by presenting a literature review encompassing the utilization of XR technologies for the condition assessment of civil structures. This study aims to provide essential information and guidelines for practitioners and researchers on using XR technologies to maintain the integrity and safety of civil structures.

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Section: Extended Reality For Structural Condition Assessment Of Civi...mentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Extended Reality (XR) for Condition Assessment of Civil Engineering Structures: A Literature Review

Çatbaş

Luleci

Zakaria

et al. 2022

Sensors

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“…Mixed reality is one of the key enablers of the digital revolution the world is currently undergoing. Although a number of studies in the past relied on virtual reality-based solutions (Luleci et al, 2022), augmented reality holds a greater promise for future inspection applications as it overlays digital content and information onto the physical world. It is indisputable that this technology will see extensive use in the future inspection process to assist the human inspectors in quick and accurate decision-making (Xu et al, 2021b,a;Aguero et al, 2021).…”

Section: Inspection Solutions Based On Aiassisted Mixed Realitymentioning

confidence: 99%

Artificial intelligence in civil infrastructure health monitoring—Historical perspectives, current trends, and future visions

Mondal

Chen

2022

Front. Built Environ.

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Over the past 2 decades, the use of artificial intelligence (AI) has exponentially increased toward complete automation of structural inspection and assessment tasks. This trend will continue to rise in image processing as unmanned aerial systems (UAS) and the internet of things (IoT) markets are expected to expand at a compound annual growth rate of 57.5% and 26%, respectively, from 2021 to 2028. This paper aims to catalog the milestone development work, summarize the current research trends, and envision a few future research directions in the innovative application of AI in civil infrastructure health monitoring. A blow-by-blow account of the major technology progression in this research field is provided in a chronological order. Detailed applications, key contributions, and performance measures of each milestone publication are presented. Representative technologies are detailed to demonstrate current research trends. A road map for future research is outlined to address contemporary issues such as explainable and physics-informed AI. This paper will provide readers with a lucid memoir of the historical progress, a good sense of the current trends, and a clear vision for future research.

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“…Additionally, SHM could benefit from Virtual Reality (VR) technology, as time-consuming field trips and dangerous site inspections of large infrastructures by teams of experts could be replaced by “virtual visits” operated through a VR platform [ 97 ].…”

Section: Trends and Perspectivesmentioning

confidence: 99%

Non-Destructive Health Monitoring of Structural Polymer Composites: Trends and Perspectives in the Digital Era

Chaki

Krawczak

2022

Materials

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Non-destructive testing (NDT) techniques are usually used for the characterisation of defects arising in polymer composites during manufacturing or in-service use. However, each of these NDT techniques cannot always allow a full diagnosis of the material’s or component’s structural health. Thus, several techniques have to be combined in order to improve the diagnosis of the damaged state of composite structures and their evolution during the part’s life span. This opinion paper proposes a critical overview of the use and applicability of these NDT techniques for the detection and characterisation of damage to structural composite materials in view of in-service performance assessment and residual durability prognosis. It also addresses some current trends of structural health monitoring (SHM) of these materials, such as sensor–actuator embedding and NDT data fusion, and draws future perspectives on how composite SHM could evolve in the digital era, taking advantage of artificial intelligence, Internet of Things and big data to implement digital twins.

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Structural Health Monitoring of a Foot Bridge in Virtual Reality Environment

Cited by 18 publications

References 9 publications

Extended Reality (XR) for Condition Assessment of Civil Engineering Structures: A Literature Review

Extended Reality (XR) for Condition Assessment of Civil Engineering Structures: A Literature Review

Artificial intelligence in civil infrastructure health monitoring—Historical perspectives, current trends, and future visions

Non-Destructive Health Monitoring of Structural Polymer Composites: Trends and Perspectives in the Digital Era

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