Defects Detection and Identification in Adhesively Bonded Joints between CFRP Laminate and Reinforced Concrete Beam Using Acousto-Ultrasonic Technique
Adhesively bonded composite reinforcements have been increasingly used in civil engineering since the 1980s. They depend on the effective transfer of forces throughout the adhesive joint that may be affected by defects or damages. It is therefore necessary to provide methods to detect and/or identif...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Journal of Composites Science |
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| Online Access: | https://www.mdpi.com/2504-477X/6/11/334 |
| _version_ | 1797467744480788480 |
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| author | Cheikh A. T. Sarr Sylvain Chataigner Laurent Gaillet Nathalie Godin |
| author_facet | Cheikh A. T. Sarr Sylvain Chataigner Laurent Gaillet Nathalie Godin |
| author_sort | Cheikh A. T. Sarr |
| collection | DOAJ |
| description | Adhesively bonded composite reinforcements have been increasingly used in civil engineering since the 1980s. They depend on the effective transfer of forces throughout the adhesive joint that may be affected by defects or damages. It is therefore necessary to provide methods to detect and/or identify these defects present in the bonded joints without affecting their future use. This should be carried out through nondestructive methods (NDT) and should be able to discriminate the different types of defects that may be encountered. The acousto-ultrasonic technique shows good potential to answer to this challenge, as illustrated in recent studies led on small-scale model samples. In this paper, we assess the robustness of this methodology on larger scale samples using reinforced concrete beams (RC beam), that is a mandatory step prior to on-site applications. A mono-parametric analysis allows the detection of all types of defects using a simple criterion set. For the identification, it was necessary to conduct a data-driven strategy by means of a Principal Component Analysis (PCA) and a random forest (RF) method used from extracted parameters. |
| first_indexed | 2024-03-09T18:58:04Z |
| format | Article |
| id | doaj.art-d49aa78591dd4974b133363df02a0554 |
| institution | Directory Open Access Journal |
| issn | 2504-477X |
| language | English |
| last_indexed | 2024-03-09T18:58:04Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Composites Science |
| spelling | doaj.art-d49aa78591dd4974b133363df02a05542023-11-24T05:20:33ZengMDPI AGJournal of Composites Science2504-477X2022-11-0161133410.3390/jcs6110334Defects Detection and Identification in Adhesively Bonded Joints between CFRP Laminate and Reinforced Concrete Beam Using Acousto-Ultrasonic TechniqueCheikh A. T. Sarr0Sylvain Chataigner1Laurent Gaillet2Nathalie Godin3Structures Métalliques et à Câbles (SMC), Dept Matériaux et Structures (MAST), Université Gustave Eiffel, Route de Bouaye, 44341 Bouguenais, FranceStructures Métalliques et à Câbles (SMC), Dept Matériaux et Structures (MAST), Université Gustave Eiffel, Route de Bouaye, 44341 Bouguenais, FranceStructures Métalliques et à Câbles (SMC), Dept Matériaux et Structures (MAST), Université Gustave Eiffel, Route de Bouaye, 44341 Bouguenais, FranceMATEIS, UMR5510, INSA Lyon, Université Claude Bernard Lyon 1, 69621 Villeurbanne, FranceAdhesively bonded composite reinforcements have been increasingly used in civil engineering since the 1980s. They depend on the effective transfer of forces throughout the adhesive joint that may be affected by defects or damages. It is therefore necessary to provide methods to detect and/or identify these defects present in the bonded joints without affecting their future use. This should be carried out through nondestructive methods (NDT) and should be able to discriminate the different types of defects that may be encountered. The acousto-ultrasonic technique shows good potential to answer to this challenge, as illustrated in recent studies led on small-scale model samples. In this paper, we assess the robustness of this methodology on larger scale samples using reinforced concrete beams (RC beam), that is a mandatory step prior to on-site applications. A mono-parametric analysis allows the detection of all types of defects using a simple criterion set. For the identification, it was necessary to conduct a data-driven strategy by means of a Principal Component Analysis (PCA) and a random forest (RF) method used from extracted parameters.https://www.mdpi.com/2504-477X/6/11/334acousto-ultrasonicnon-destructive technique (NDT)adhesively bonded jointdiagnosticdata-driven modelPCA |
| spellingShingle | Cheikh A. T. Sarr Sylvain Chataigner Laurent Gaillet Nathalie Godin Defects Detection and Identification in Adhesively Bonded Joints between CFRP Laminate and Reinforced Concrete Beam Using Acousto-Ultrasonic Technique Journal of Composites Science acousto-ultrasonic non-destructive technique (NDT) adhesively bonded joint diagnostic data-driven model PCA |
| title | Defects Detection and Identification in Adhesively Bonded Joints between CFRP Laminate and Reinforced Concrete Beam Using Acousto-Ultrasonic Technique |
| title_full | Defects Detection and Identification in Adhesively Bonded Joints between CFRP Laminate and Reinforced Concrete Beam Using Acousto-Ultrasonic Technique |
| title_fullStr | Defects Detection and Identification in Adhesively Bonded Joints between CFRP Laminate and Reinforced Concrete Beam Using Acousto-Ultrasonic Technique |
| title_full_unstemmed | Defects Detection and Identification in Adhesively Bonded Joints between CFRP Laminate and Reinforced Concrete Beam Using Acousto-Ultrasonic Technique |
| title_short | Defects Detection and Identification in Adhesively Bonded Joints between CFRP Laminate and Reinforced Concrete Beam Using Acousto-Ultrasonic Technique |
| title_sort | defects detection and identification in adhesively bonded joints between cfrp laminate and reinforced concrete beam using acousto ultrasonic technique |
| topic | acousto-ultrasonic non-destructive technique (NDT) adhesively bonded joint diagnostic data-driven model PCA |
| url | https://www.mdpi.com/2504-477X/6/11/334 |
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