A semantic modeling approach for the automated detection and interpretation of structural damage

Hamdan, Al‐Hakam; Taraben, Jakob; Helmrich, Marcel; Mansperger, Tobias; Morgenthal, Guido; Scherer, Raimar J.

doi:10.1016/j.autcon.2021.103739

Cited by 36 publications

(23 citation statements)

References 48 publications

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“…However, in-depth information on how to exchange damage data with third party software is not provided in this study. Hamdan et al developed a framework for bridge assessment based on a linked model approach [40]. Such linked models have the disadvantage of data dispersion.…”

Section: Damage Data Applicationsmentioning

confidence: 99%

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A BIM Based Framework for Damage Segmentation, Modeling, and Visualization Using IFC

2022

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Paper-based data acquisition and manual transfer between incompatible software or data formats during inspections of bridges, as done currently, are time-consuming, error-prone, cumbersome, and lead to information loss. A fully digitized workflow using open data formats would reduce data loss, efforts, and the costs of future inspections. On the one hand, existing studies proposed methods to automatize data acquisition and visualization for inspections. These studies lack an open standard to make the gathered data available for other processes. On the other hand, several studies discuss data structures for exchanging damage information among different stakeholders. However, those studies do not cover the process of automatic data acquisition and transfer. This study focuses on a framework that incorporates automatic damage data acquisition, transfer, and a damage information model for data exchange. This enables inspectors to use damage data for subsequent analyses and simulations. The proposed framework shows the potentials for a comprehensive damage information model and related (semi-)automatic data acquisition and processing.

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Section: Damage Data Applicationsmentioning

confidence: 99%

“…Several frameworks that generate point clouds and damage information from images and perform FEAs exist [39,40]. However, these models focus on supporting FEA only; other applications or domains have not been considered.…”

Section: Problem Statements and Objectivesmentioning

confidence: 99%

A BIM Based Framework for Damage Segmentation, Modeling, and Visualization Using IFC

2022

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“…However, a data model to exhange damage data with third party software is not defined in this study. Hamdan et al developed a framework for bridge assessment based on a linked model approach [26]. Such linked models have the disadvantage of data dispersion and for later data exchange it is beneficial if all data is stored in a single file.…”

Section: Damage Data Applicationsmentioning

confidence: 99%

“…Several frameworks that generate point clouds and damage information from images and perform FEAs exist [26,25]. However, these models focus on supporting FEA only; other applications or domains have not been considered.…”

Section: Problem Statements and Objectivesmentioning

confidence: 99%

A BIM Based Framework for Damage Segmentation, Storage, and Visualization

Artus¹,

Alabassy²,

Koch³

2022

Preprint

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Current bridge inspection practices rely on paper-based data acquisition, digitization, and multiple conversions in between incompatible formats to facilitate data exchange. This practice is time-consuming, error-prone, cumbersome, and leads to information loss. One aim for future inspection procedures is to have a fully digitized workflow that achieves loss-free data exchange, which lowers costs and offers higher efficiency. On the one hand, existing studies proposed methods to automatize data acquisition and visualization for inspections. These studies lack an open standard to make the gathered data available for other processes. On the other hand, several studies discuss data structures for exchanging damage information through out different stakeholders. However, those studies do not cover the process of automatic data acquisition and transfer. This study focused on a framework that incorporates automatic damage data acquisition, transfer, and a damage information model for data exchange. This enables inspectors to use damage data for subsequent analyses and simulations. The proposed framework shows the potentials for a comprehensive damage information model and related (semi-)automatic data acquisition and processing.

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“…Ontology-based methods were studied to improve information exchange and maintenance management of bridge networks [14,50], road networks [51], and highway construction inspection [22]. Considering the importance of defect information for infrastructure maintenance, ontologies were investigated to facilitate defect data sharing and management [52,53] as well as automated detection, interpretation and diagnosis of structural damages [54,55]. Additionally, researchers tried to integrate heterogeneous information using semantic web technologies to build decision support systems for highway asset management [56], and urban infrastructure inter-asset management [57].…”

Section: Data Models and Ontologies For Civil Infrastructurementioning

confidence: 99%

Ontology-based modelling of lifecycle underground utility information to support operation and maintenance

Ming-zhu

2021

Automation in Construction

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A semantic modeling approach for the automated detection and interpretation of structural damage

Cited by 36 publications

References 48 publications

A BIM Based Framework for Damage Segmentation, Modeling, and Visualization Using IFC

A BIM Based Framework for Damage Segmentation, Modeling, and Visualization Using IFC

A BIM Based Framework for Damage Segmentation, Storage, and Visualization

Ontology-based modelling of lifecycle underground utility information to support operation and maintenance

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