Automated condition assessment of concrete bridges with digital imaging

Adhikari, R.S.; Bagchi, Ashutosh; Moselhi, Osama

doi:10.12989/sss.2014.13.6.901

Cited by 11 publications

(2 citation statements)

References 21 publications

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“…Adoption of AI based tools for NDE and Structural Health Monitoring (SHM) has already initiated by many works in academic world [19][20][21][22][23] and some industry initiatives [7]. However, wide transition of these tools to NDE industries is slower than desired.…”

Section: Artifactual Intelligencementioning

confidence: 99%

Advancements in Radiographic Evaluation Through the Migration into NDE 4.0

Saboonchi

Blanchette

Hayes³

2021

J Nondestruct Eval

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The challenges presented by the global pandemic and slump in oil prices have imposed costly avoidance measures and delayed project timeliness, but it also has created the opportunity for innovation conditions in industrial non-destructive testing. The evolutional path leveraged by Industry 4.0, present sustainable offerings of robotic platforms, digital solutions and connected devices commonly known as the Internet of Things (IoT) that may assist in recapturing some of the current losses. The landscape is broad with staggered adoptions. An overview of the Industrial Revolutions, related developments in NDE 4.0 and specific focus on North American radiography in the petroleum industry is highlighted. Additionally, focusing on the importance of shared transparency and burden throughout the value-chain to ensure efficacy throughout the migration, and the human contributor for collaborative transition and skills required for the future. The evolutional path of Industrial revolutions leads to Industry 4.0 which presents opportunities with Artificial Intelligence, and connected devices commonly known as the Internet of Things (IoT). This article focuses on three major issues for consideration in the development of a strategic plan to capitalize on the advancements of digital radiography in the petroleum sector. The components are the technological NDE 4.0 transformation, the need for a new and realistic perspective of digital radiography, and the challenges of developing a workforce to adapt to the transition of NDE 4.0.

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Section: Artifactual Intelligencementioning

confidence: 99%

Advancements in Radiographic Evaluation Through the Migration into NDE 4.0

Saboonchi

Blanchette

Hayes³

2021

J Nondestruct Eval

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“…Halfawy and Hengmeechai [127] embedded the visionbased defection recognition system into the closed circuit television (CCTV) system mounted in the sewer to inspect its defections automatically. Adhikari et al [128] presented an approach of automated condition assessment of concrete bridges based on digital image analyses.…”

Section: Crack Inspection and Characterizationmentioning

confidence: 99%

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

2016

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In the past two decades, a significant number of innovative sensing and monitoring systems based on the machine vision-based technology have been exploited in the field of structural health monitoring (SHM). This technology has some inherent distinctive advantages such as noncontact, nondestructive, long distance, high precision, immunity to electromagnetic interference, and large-range and multiple-target monitoring. A lot of machine vision-based structural dynamic measurement and structural state inspection methods have been proposed. Real-world applications are also carried out to measure the structural physical parameters such as the displacement, strain/stress, rotation, vibration, crack, and spalling. The purpose of this review article is devoted to presenting a summary of the basic theories and practical applications of the machine vision-based technology employed in structural monitoring as well as its systematic error sources and integration with other modern sensing techniques.

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End-to-end concrete appearance analysis based on pixel-wise semantic segmentation and CIE Lab

Hao

2022

Cement and Concrete Research

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Automated condition assessment of concrete bridges with digital imaging

Cited by 11 publications

References 21 publications

Advancements in Radiographic Evaluation Through the Migration into NDE 4.0

Advancements in Radiographic Evaluation Through the Migration into NDE 4.0

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

End-to-end concrete appearance analysis based on pixel-wise semantic segmentation and CIE Lab

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