Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique
Grouting ducts (containing steel strands) are widely used to increase the structural strengths of infrastructures. The determination of the steel strand’s integrity inside of ducts and the grouting quality are important for a strength evaluation of the structure. In this study, a capacitiv...
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| Format: | Article |
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MDPI AG
2019-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/11/2564 |
| _version_ | 1798035469168017408 |
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| author | Nan Li Mingchen Cao Hangben Du Cunfu He Bin Wu |
| author_facet | Nan Li Mingchen Cao Hangben Du Cunfu He Bin Wu |
| author_sort | Nan Li |
| collection | DOAJ |
| description | Grouting ducts (containing steel strands) are widely used to increase the structural strengths of infrastructures. The determination of the steel strand’s integrity inside of ducts and the grouting quality are important for a strength evaluation of the structure. In this study, a capacitive sensing technique was applied to identify the cross-sectional distribution of the steel strands. The distribution was expressed in polar coordinates in an external post-tensioned pre-stressed duct model. An improved capacitive sensor structure was designed, which consisted of four electrodes, and different electrode-pairs were used to determine various locations’ information of the steel strands. Two rounds of measurements were conducted using the designed sensor to detect the angle (<i>θ</i>) and center distance (<i>r</i>) of the steel strand in the duct. The simulated and experimental results are presented and analyzed. In general, it is difficult to locate the angle of a steel strand directly from first-round capacitance measurements by analyzing the experimental results. Our method based on Q-factor analysis was presented for the position detection of a steel bar in an external post-tensioned pre-stressed duct. The center distance of the steel bar could be identified by second-round capacitance measurements. The processed results verified the effectiveness of the proposed capacitive sensor structure. Thus, the capacitive sensing technique exhibited potential for steel strand cross-section distribution detection in external post-tensioned pre-stressed ducts. |
| first_indexed | 2024-04-11T20:57:40Z |
| format | Article |
| id | doaj.art-c010158abcb44d57952025f67343ecf7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T20:57:40Z |
| publishDate | 2019-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c010158abcb44d57952025f67343ecf72022-12-22T04:03:37ZengMDPI AGSensors1424-82202019-06-011911256410.3390/s19112564s19112564Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing TechniqueNan Li0Mingchen Cao1Hangben Du2Cunfu He3Bin Wu4School of Automation, Northwestern Polytechnical University, Xi’an 710071, ChinaState Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Automation, Northwestern Polytechnical University, Xi’an 710071, ChinaNDT&E Research Centre, Beijing University of Technology, Beijing 100124, ChinaNDT&E Research Centre, Beijing University of Technology, Beijing 100124, ChinaGrouting ducts (containing steel strands) are widely used to increase the structural strengths of infrastructures. The determination of the steel strand’s integrity inside of ducts and the grouting quality are important for a strength evaluation of the structure. In this study, a capacitive sensing technique was applied to identify the cross-sectional distribution of the steel strands. The distribution was expressed in polar coordinates in an external post-tensioned pre-stressed duct model. An improved capacitive sensor structure was designed, which consisted of four electrodes, and different electrode-pairs were used to determine various locations’ information of the steel strands. Two rounds of measurements were conducted using the designed sensor to detect the angle (<i>θ</i>) and center distance (<i>r</i>) of the steel strand in the duct. The simulated and experimental results are presented and analyzed. In general, it is difficult to locate the angle of a steel strand directly from first-round capacitance measurements by analyzing the experimental results. Our method based on Q-factor analysis was presented for the position detection of a steel bar in an external post-tensioned pre-stressed duct. The center distance of the steel bar could be identified by second-round capacitance measurements. The processed results verified the effectiveness of the proposed capacitive sensor structure. Thus, the capacitive sensing technique exhibited potential for steel strand cross-section distribution detection in external post-tensioned pre-stressed ducts.https://www.mdpi.com/1424-8220/19/11/2564grouting ductcapacitive sensorcross section distribution detectingmeasurement |
| spellingShingle | Nan Li Mingchen Cao Hangben Du Cunfu He Bin Wu Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique Sensors grouting duct capacitive sensor cross section distribution detecting measurement |
| title | Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique |
| title_full | Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique |
| title_fullStr | Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique |
| title_full_unstemmed | Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique |
| title_short | Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique |
| title_sort | detection of single steel strand distribution in grouting duct based on capacitive sensing technique |
| topic | grouting duct capacitive sensor cross section distribution detecting measurement |
| url | https://www.mdpi.com/1424-8220/19/11/2564 |
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