Crack Detection of Reinforced Concrete Structures Based on BOFDA and FBG Sensors
Reinforced concrete structural elements, as an important component of buildings and structures, require inspection for the purposes of crack detection which is an important part of structural health monitoring. Now existing crack detection methods usually use a single technology and can only detect...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2018/6563537 |
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| author | Qinghua Zhang Ziming Xiong |
| author_facet | Qinghua Zhang Ziming Xiong |
| author_sort | Qinghua Zhang |
| collection | DOAJ |
| description | Reinforced concrete structural elements, as an important component of buildings and structures, require inspection for the purposes of crack detection which is an important part of structural health monitoring. Now existing crack detection methods usually use a single technology and can only detect internal or external cracks. In this paper, the authors propose a new sensing system combining BOFDA (Brillouin optical frequency-domain analysis) and FBG (fiber Bragg grating) technology, which are used to detect internal and surface cracks and their development in reinforced concrete structures, and an attempt is made to estimate the width of surface cracks. In these experiments, a special reinforced concrete beam structure was designed by the author for crack detection under load. Four continuous distributed optical fibers are fixed on the steel skeleton, which is located within the reinforced concrete beam. Three FBG sensors are fixed on the lower surface of the beam, near its centre. By analysing the sensor data, it can be found that the BOFDA-distributed fiber can be used to detect internal cracking before surface cracking, and the difference between scans can be used to judge the time of onset of internal cracking, but the relative error in position is about 5%, while the FBG sensor can detect the cracking time of microcracks on the lower surface in near-real-time and can be used to calculate the crack width. Through the experiment, it is found that if the combination of BOFDA and FBG technology is adopted, we can initially use the strain data obtained by multiple groups of BOFDA monitoring to predict the general location of the internal cracks, then to monitor the exact location of the surface cracks by FBG in the medium term, and to estimate the width of the final expansion of the cracks finally. |
| format | Article |
| id | doaj-art-62031fc0a976482fa53c2f51bd3ded4c |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-62031fc0a976482fa53c2f51bd3ded4c2025-02-03T01:28:46ZengWileyShock and Vibration1070-96221875-92032018-01-01201810.1155/2018/65635376563537Crack Detection of Reinforced Concrete Structures Based on BOFDA and FBG SensorsQinghua Zhang0Ziming Xiong1College of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, ChinaCollege of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, ChinaReinforced concrete structural elements, as an important component of buildings and structures, require inspection for the purposes of crack detection which is an important part of structural health monitoring. Now existing crack detection methods usually use a single technology and can only detect internal or external cracks. In this paper, the authors propose a new sensing system combining BOFDA (Brillouin optical frequency-domain analysis) and FBG (fiber Bragg grating) technology, which are used to detect internal and surface cracks and their development in reinforced concrete structures, and an attempt is made to estimate the width of surface cracks. In these experiments, a special reinforced concrete beam structure was designed by the author for crack detection under load. Four continuous distributed optical fibers are fixed on the steel skeleton, which is located within the reinforced concrete beam. Three FBG sensors are fixed on the lower surface of the beam, near its centre. By analysing the sensor data, it can be found that the BOFDA-distributed fiber can be used to detect internal cracking before surface cracking, and the difference between scans can be used to judge the time of onset of internal cracking, but the relative error in position is about 5%, while the FBG sensor can detect the cracking time of microcracks on the lower surface in near-real-time and can be used to calculate the crack width. Through the experiment, it is found that if the combination of BOFDA and FBG technology is adopted, we can initially use the strain data obtained by multiple groups of BOFDA monitoring to predict the general location of the internal cracks, then to monitor the exact location of the surface cracks by FBG in the medium term, and to estimate the width of the final expansion of the cracks finally.http://dx.doi.org/10.1155/2018/6563537 |
| spellingShingle | Qinghua Zhang Ziming Xiong Crack Detection of Reinforced Concrete Structures Based on BOFDA and FBG Sensors Shock and Vibration |
| title | Crack Detection of Reinforced Concrete Structures Based on BOFDA and FBG Sensors |
| title_full | Crack Detection of Reinforced Concrete Structures Based on BOFDA and FBG Sensors |
| title_fullStr | Crack Detection of Reinforced Concrete Structures Based on BOFDA and FBG Sensors |
| title_full_unstemmed | Crack Detection of Reinforced Concrete Structures Based on BOFDA and FBG Sensors |
| title_short | Crack Detection of Reinforced Concrete Structures Based on BOFDA and FBG Sensors |
| title_sort | crack detection of reinforced concrete structures based on bofda and fbg sensors |
| url | http://dx.doi.org/10.1155/2018/6563537 |
| work_keys_str_mv | AT qinghuazhang crackdetectionofreinforcedconcretestructuresbasedonbofdaandfbgsensors AT zimingxiong crackdetectionofreinforcedconcretestructuresbasedonbofdaandfbgsensors |