Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method
Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Shibano, Kazuma [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
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| Anmerkung: |
© The International Society of Paddy and Water Environment Engineering 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Paddy and water environment - Springer Nature Singapore, 2003, 22(2024), 2 vom: 15. Feb., Seite 257-269 |
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| Übergeordnetes Werk: |
volume:22 ; year:2024 ; number:2 ; day:15 ; month:02 ; pages:257-269 |
| Links: |
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| DOI / URN: |
10.1007/s10333-023-00965-3 |
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SPR05514084X |
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| 520 | |a Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields; nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. The characteristics of surface damage which are quantitatively evaluated using point cloud information, geometric information and intensity parameter are investigated. The types of detected damage are efflorescence and cracks. It is investigated whether point clouds generated from a single scan or multiple scans are more effective for highly accurate detection. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage. | ||
| 650 | 4 | |a Laser scanning method |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Three-dimensional point clouds |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Concrete headworks |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Surface damage |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Chiyoda, Atsushi |4 aut | |
| 700 | 1 | |a Ito, Hisaya |4 aut | |
| 700 | 1 | |a Suzuki, Tetsuya |4 aut | |
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10.1007/s10333-023-00965-3 doi (DE-627)SPR05514084X (SPR)s10333-023-00965-3-e DE-627 ger DE-627 rakwb eng 690 VZ 48.34 bkl Shibano, Kazuma verfasserin aut Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The International Society of Paddy and Water Environment Engineering 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields; nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. The characteristics of surface damage which are quantitatively evaluated using point cloud information, geometric information and intensity parameter are investigated. The types of detected damage are efflorescence and cracks. It is investigated whether point clouds generated from a single scan or multiple scans are more effective for highly accurate detection. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage. Laser scanning method (dpeaa)DE-He213 Three-dimensional point clouds (dpeaa)DE-He213 Concrete headworks (dpeaa)DE-He213 Surface damage (dpeaa)DE-He213 RANSAC algorithm (dpeaa)DE-He213 Morozova, Nadezhda aut Ito, Yuji aut Shimamoto, Yuma aut Tachibana, Yuki aut Suematsu, Kakutaro aut Chiyoda, Atsushi aut Ito, Hisaya aut Suzuki, Tetsuya aut Enthalten in Paddy and water environment Springer Nature Singapore, 2003 22(2024), 2 vom: 15. Feb., Seite 257-269 (DE-627)363745564 (DE-600)2104594-X 1611-2504 nnns volume:22 year:2024 number:2 day:15 month:02 pages:257-269 https://dx.doi.org/10.1007/s10333-023-00965-3 lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.34 VZ AR 22 2024 2 15 02 257-269 |
| spelling |
10.1007/s10333-023-00965-3 doi (DE-627)SPR05514084X (SPR)s10333-023-00965-3-e DE-627 ger DE-627 rakwb eng 690 VZ 48.34 bkl Shibano, Kazuma verfasserin aut Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The International Society of Paddy and Water Environment Engineering 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields; nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. The characteristics of surface damage which are quantitatively evaluated using point cloud information, geometric information and intensity parameter are investigated. The types of detected damage are efflorescence and cracks. It is investigated whether point clouds generated from a single scan or multiple scans are more effective for highly accurate detection. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage. Laser scanning method (dpeaa)DE-He213 Three-dimensional point clouds (dpeaa)DE-He213 Concrete headworks (dpeaa)DE-He213 Surface damage (dpeaa)DE-He213 RANSAC algorithm (dpeaa)DE-He213 Morozova, Nadezhda aut Ito, Yuji aut Shimamoto, Yuma aut Tachibana, Yuki aut Suematsu, Kakutaro aut Chiyoda, Atsushi aut Ito, Hisaya aut Suzuki, Tetsuya aut Enthalten in Paddy and water environment Springer Nature Singapore, 2003 22(2024), 2 vom: 15. Feb., Seite 257-269 (DE-627)363745564 (DE-600)2104594-X 1611-2504 nnns volume:22 year:2024 number:2 day:15 month:02 pages:257-269 https://dx.doi.org/10.1007/s10333-023-00965-3 lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.34 VZ AR 22 2024 2 15 02 257-269 |
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10.1007/s10333-023-00965-3 doi (DE-627)SPR05514084X (SPR)s10333-023-00965-3-e DE-627 ger DE-627 rakwb eng 690 VZ 48.34 bkl Shibano, Kazuma verfasserin aut Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The International Society of Paddy and Water Environment Engineering 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields; nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. The characteristics of surface damage which are quantitatively evaluated using point cloud information, geometric information and intensity parameter are investigated. The types of detected damage are efflorescence and cracks. It is investigated whether point clouds generated from a single scan or multiple scans are more effective for highly accurate detection. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage. Laser scanning method (dpeaa)DE-He213 Three-dimensional point clouds (dpeaa)DE-He213 Concrete headworks (dpeaa)DE-He213 Surface damage (dpeaa)DE-He213 RANSAC algorithm (dpeaa)DE-He213 Morozova, Nadezhda aut Ito, Yuji aut Shimamoto, Yuma aut Tachibana, Yuki aut Suematsu, Kakutaro aut Chiyoda, Atsushi aut Ito, Hisaya aut Suzuki, Tetsuya aut Enthalten in Paddy and water environment Springer Nature Singapore, 2003 22(2024), 2 vom: 15. Feb., Seite 257-269 (DE-627)363745564 (DE-600)2104594-X 1611-2504 nnns volume:22 year:2024 number:2 day:15 month:02 pages:257-269 https://dx.doi.org/10.1007/s10333-023-00965-3 lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.34 VZ AR 22 2024 2 15 02 257-269 |
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10.1007/s10333-023-00965-3 doi (DE-627)SPR05514084X (SPR)s10333-023-00965-3-e DE-627 ger DE-627 rakwb eng 690 VZ 48.34 bkl Shibano, Kazuma verfasserin aut Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The International Society of Paddy and Water Environment Engineering 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields; nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. The characteristics of surface damage which are quantitatively evaluated using point cloud information, geometric information and intensity parameter are investigated. The types of detected damage are efflorescence and cracks. It is investigated whether point clouds generated from a single scan or multiple scans are more effective for highly accurate detection. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage. Laser scanning method (dpeaa)DE-He213 Three-dimensional point clouds (dpeaa)DE-He213 Concrete headworks (dpeaa)DE-He213 Surface damage (dpeaa)DE-He213 RANSAC algorithm (dpeaa)DE-He213 Morozova, Nadezhda aut Ito, Yuji aut Shimamoto, Yuma aut Tachibana, Yuki aut Suematsu, Kakutaro aut Chiyoda, Atsushi aut Ito, Hisaya aut Suzuki, Tetsuya aut Enthalten in Paddy and water environment Springer Nature Singapore, 2003 22(2024), 2 vom: 15. Feb., Seite 257-269 (DE-627)363745564 (DE-600)2104594-X 1611-2504 nnns volume:22 year:2024 number:2 day:15 month:02 pages:257-269 https://dx.doi.org/10.1007/s10333-023-00965-3 lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.34 VZ AR 22 2024 2 15 02 257-269 |
| allfieldsSound |
10.1007/s10333-023-00965-3 doi (DE-627)SPR05514084X (SPR)s10333-023-00965-3-e DE-627 ger DE-627 rakwb eng 690 VZ 48.34 bkl Shibano, Kazuma verfasserin aut Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The International Society of Paddy and Water Environment Engineering 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields; nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. The characteristics of surface damage which are quantitatively evaluated using point cloud information, geometric information and intensity parameter are investigated. The types of detected damage are efflorescence and cracks. It is investigated whether point clouds generated from a single scan or multiple scans are more effective for highly accurate detection. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage. Laser scanning method (dpeaa)DE-He213 Three-dimensional point clouds (dpeaa)DE-He213 Concrete headworks (dpeaa)DE-He213 Surface damage (dpeaa)DE-He213 RANSAC algorithm (dpeaa)DE-He213 Morozova, Nadezhda aut Ito, Yuji aut Shimamoto, Yuma aut Tachibana, Yuki aut Suematsu, Kakutaro aut Chiyoda, Atsushi aut Ito, Hisaya aut Suzuki, Tetsuya aut Enthalten in Paddy and water environment Springer Nature Singapore, 2003 22(2024), 2 vom: 15. Feb., Seite 257-269 (DE-627)363745564 (DE-600)2104594-X 1611-2504 nnns volume:22 year:2024 number:2 day:15 month:02 pages:257-269 https://dx.doi.org/10.1007/s10333-023-00965-3 lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.34 VZ AR 22 2024 2 15 02 257-269 |
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Shibano, Kazuma @@aut@@ Morozova, Nadezhda @@aut@@ Ito, Yuji @@aut@@ Shimamoto, Yuma @@aut@@ Tachibana, Yuki @@aut@@ Suematsu, Kakutaro @@aut@@ Chiyoda, Atsushi @@aut@@ Ito, Hisaya @@aut@@ Suzuki, Tetsuya @@aut@@ |
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Shibano, Kazuma |
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Shibano, Kazuma ddc 690 bkl 48.34 misc Laser scanning method misc Three-dimensional point clouds misc Concrete headworks misc Surface damage misc RANSAC algorithm Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method |
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690 VZ 48.34 bkl Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method Laser scanning method (dpeaa)DE-He213 Three-dimensional point clouds (dpeaa)DE-He213 Concrete headworks (dpeaa)DE-He213 Surface damage (dpeaa)DE-He213 RANSAC algorithm (dpeaa)DE-He213 |
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ddc 690 bkl 48.34 misc Laser scanning method misc Three-dimensional point clouds misc Concrete headworks misc Surface damage misc RANSAC algorithm |
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Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method |
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Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method |
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Shibano, Kazuma Morozova, Nadezhda Ito, Yuji Shimamoto, Yuma Tachibana, Yuki Suematsu, Kakutaro Chiyoda, Atsushi Ito, Hisaya Suzuki, Tetsuya |
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evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3d point clouds by laser scanning method |
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Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method |
| abstract |
Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields; nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. The characteristics of surface damage which are quantitatively evaluated using point cloud information, geometric information and intensity parameter are investigated. The types of detected damage are efflorescence and cracks. It is investigated whether point clouds generated from a single scan or multiple scans are more effective for highly accurate detection. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage. © The International Society of Paddy and Water Environment Engineering 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields; nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. The characteristics of surface damage which are quantitatively evaluated using point cloud information, geometric information and intensity parameter are investigated. The types of detected damage are efflorescence and cracks. It is investigated whether point clouds generated from a single scan or multiple scans are more effective for highly accurate detection. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage. © The International Society of Paddy and Water Environment Engineering 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, a number of agricultural concrete infrastructures aging for a long-term period have been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields; nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. The characteristics of surface damage which are quantitatively evaluated using point cloud information, geometric information and intensity parameter are investigated. The types of detected damage are efflorescence and cracks. It is investigated whether point clouds generated from a single scan or multiple scans are more effective for highly accurate detection. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage. © The International Society of Paddy and Water Environment Engineering 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Evaluation of surface damage for in-service deteriorated agricultural concrete headworks using 3D point clouds by laser scanning method |
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Morozova, Nadezhda Ito, Yuji Shimamoto, Yuma Tachibana, Yuki Suematsu, Kakutaro Chiyoda, Atsushi Ito, Hisaya Suzuki, Tetsuya |
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Morozova, Nadezhda Ito, Yuji Shimamoto, Yuma Tachibana, Yuki Suematsu, Kakutaro Chiyoda, Atsushi Ito, Hisaya Suzuki, Tetsuya |
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10.1007/s10333-023-00965-3 |
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2024-07-03T13:38:22.267Z |
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| score |
7.4013786 |