A pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentation
Abstract Monitoring of structures’ condition plays a fundamental role in providing safety for users and extending the structures’ lifespan. The monitoring is conducted through on-site inspections by engineers thus this process is time-consuming, labor-intensive and prone to subjective engineering op...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-12-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02839-z |
| _version_ | 1797377174733324288 |
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| author | Karolina Tomaszkiewicz Tomasz Owerko |
| author_facet | Karolina Tomaszkiewicz Tomasz Owerko |
| author_sort | Karolina Tomaszkiewicz |
| collection | DOAJ |
| description | Abstract Monitoring of structures’ condition plays a fundamental role in providing safety for users and extending the structures’ lifespan. The monitoring is conducted through on-site inspections by engineers thus this process is time-consuming, labor-intensive and prone to subjective engineering opinions. Detecting damage using machine learning algorithms on images can support engineers’ work, especially for early damages which are difficult to see with the human eye. This article is focused on the concrete crack detection problem in engineering structural elements. Despite the availability of several concrete crack detection datasets, no dataset allows semantic segmentation of cracks narrower than 0.3 mm (the crack width limit for typical engineering structures elements and environmental conditions according to EC 1992-1-1) and the ability for crack classification is limited. The provided open dataset represents only cracks below the crack width limit of 0.3mm, which do not yet indicate concrete elements failure. It is dedicated for early crack classification and segmentation, so that damage protection can be taken at an early stage to prevent structural element damages. |
| first_indexed | 2024-03-08T19:48:57Z |
| format | Article |
| id | doaj.art-0538c43ee1cb4fc9bf5d61ff07511b33 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-03-08T19:48:57Z |
| publishDate | 2023-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-0538c43ee1cb4fc9bf5d61ff07511b332023-12-24T12:09:38ZengNature PortfolioScientific Data2052-44632023-12-0110111210.1038/s41597-023-02839-zA pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentationKarolina Tomaszkiewicz0Tomasz Owerko1AGH University of KrakowAGH University of KrakowAbstract Monitoring of structures’ condition plays a fundamental role in providing safety for users and extending the structures’ lifespan. The monitoring is conducted through on-site inspections by engineers thus this process is time-consuming, labor-intensive and prone to subjective engineering opinions. Detecting damage using machine learning algorithms on images can support engineers’ work, especially for early damages which are difficult to see with the human eye. This article is focused on the concrete crack detection problem in engineering structural elements. Despite the availability of several concrete crack detection datasets, no dataset allows semantic segmentation of cracks narrower than 0.3 mm (the crack width limit for typical engineering structures elements and environmental conditions according to EC 1992-1-1) and the ability for crack classification is limited. The provided open dataset represents only cracks below the crack width limit of 0.3mm, which do not yet indicate concrete elements failure. It is dedicated for early crack classification and segmentation, so that damage protection can be taken at an early stage to prevent structural element damages.https://doi.org/10.1038/s41597-023-02839-z |
| spellingShingle | Karolina Tomaszkiewicz Tomasz Owerko A pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentation Scientific Data |
| title | A pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentation |
| title_full | A pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentation |
| title_fullStr | A pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentation |
| title_full_unstemmed | A pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentation |
| title_short | A pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentation |
| title_sort | pre failure narrow concrete cracks dataset for engineering structures damage classification and segmentation |
| url | https://doi.org/10.1038/s41597-023-02839-z |
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