{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T14:03:51Z","timestamp":1782309831798,"version":"3.54.5"},"reference-count":17,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T00:00:00Z","timestamp":1702252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key RD Program of China","award":["2021YFE0204200"],"award-info":[{"award-number":["2021YFE0204200"]}]},{"name":"National Key RD Program of China","award":["JSGG20210802154539015"],"award-info":[{"award-number":["JSGG20210802154539015"]}]},{"name":"Shenzhen Science and Technology Program","award":["2021YFE0204200"],"award-info":[{"award-number":["2021YFE0204200"]}]},{"name":"Shenzhen Science and Technology Program","award":["JSGG20210802154539015"],"award-info":[{"award-number":["JSGG20210802154539015"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper introduces a novel method for enhancing underground pipeline inspection, specifically addressing limitations associated with traditional closed-circuit television (CCTV) systems. These systems, commonly used for capturing visual data of sewer system deformations, heavily rely on subjective human expertise, leading to limited accuracy in detection. Furthermore, their inability to perform quantitative analyses of deformation extent hampers overall inspection effectiveness. Our proposed method leverages laser point cloud data and employs a 3D scanner for objective detection of geometric deformations in underground pipe corridors. By utilizing this approach, we enable a quantitative assessment of blockage levels, offering a significant improvement over traditional CCTV-based methods. The key advantages of our method lie in its objectivity and quantification capabilities, ultimately enhancing detection reliability, accuracy, and overall inspection efficiency.<\/jats:p>","DOI":"10.3390\/s23249761","type":"journal-article","created":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T14:12:51Z","timestamp":1702303971000},"page":"9761","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Quantitative Detection Technology for Geometric Deformation of Pipelines Based on LiDAR"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1696-3277","authenticated-orcid":false,"given":"Min","family":"Zhao","sequence":"first","affiliation":[{"name":"Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518129, China"},{"name":"School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, China"},{"name":"Institute of Robotics and the Intelligent Manufacturing, Shenzhen 518172, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zehao","family":"Fang","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518129, China"},{"name":"School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ning","family":"Ding","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518129, China"},{"name":"School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, China"},{"name":"Institute of Robotics and the Intelligent Manufacturing, Shenzhen 518172, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4407-934X","authenticated-orcid":false,"given":"Nan","family":"Li","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518129, China"},{"name":"School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, China"},{"name":"Institute of Robotics and the Intelligent Manufacturing, Shenzhen 518172, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tengfei","family":"Su","sequence":"additional","affiliation":[{"name":"Shenzhen Water SCI&Tech. Development Co., Ltd., Shenzhen 518035, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huihuan","family":"Qian","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518129, China"},{"name":"School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, China"},{"name":"Institute of Robotics and the Intelligent Manufacturing, Shenzhen 518172, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"103721","DOI":"10.1016\/j.engappai.2020.103721","article-title":"A state of the art review on condition assessment models developed for sewer pipelines","volume":"93","author":"Hawari","year":"2020","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"109111","DOI":"10.1016\/j.buildenv.2022.109111","article-title":"Automatic fault diagnosis algorithm for hot water pipes based on infrared thermal images","volume":"218","author":"Guan","year":"2022","journal-title":"Build. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1109\/TASE.2019.2941848","article-title":"Toward automatic subsurface pipeline mapping by fusing a ground-penetrating radar and a camera","volume":"17","author":"Li","year":"2019","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2150030","DOI":"10.1142\/S0218001421500300","article-title":"Defect identification of pipeline ultrasonic inspection based on multi-feature fusion and multi-criteria feature evaluation","volume":"35","author":"Pan","year":"2021","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"key":"ref_5","first-page":"1","article-title":"Analysis of magnetic-flux leakage (MFL) data for pipeline corrosion assessment","volume":"56","author":"Peng","year":"2020","journal-title":"IEEE Trans. Magn."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ma, Q., Tian, G., Zeng, Y., Li, R., Song, H., Wang, Z., Gao, B., and Zeng, K. (2021). Pipeline in-line inspection method, instrumentation and data management. Sensors, 21.","DOI":"10.3390\/s21113862"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"18","DOI":"10.21014\/acta_imeko.v9i1.744","article-title":"Optical metrology applied in CCTV inspection in drain and sewer systems","volume":"9","author":"Martins","year":"2020","journal-title":"Acta IMEKO"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1007\/s40684-021-00343-6","article-title":"State of the art in defect detection based on machine vision","volume":"9","author":"Ren","year":"2022","journal-title":"Int. J. Precis. Eng. Manuf.-Green Technol."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Li, Y., Wang, H., Dang, L.M., Song, H.K., and Moon, H. (2022). Vision-based defect inspection and condition assessment for sewer pipes: A comprehensive survey. Sensors, 22.","DOI":"10.3390\/s22072722"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.compind.2018.03.020","article-title":"Utilizing text recognition for the defects extraction in sewers CCTV inspection videos","volume":"99","author":"Dang","year":"2018","journal-title":"Comput. Ind."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.autcon.2018.08.006","article-title":"Automated detection of sewer pipe defects in closed-circuit television images using deep learning techniques","volume":"95","author":"Cheng","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"109020","DOI":"10.1016\/j.measurement.2021.109020","article-title":"A steerable pyramid autoencoder based framework for anomaly frame detection of water pipeline CCTV inspection","volume":"174","author":"Jiao","year":"2021","journal-title":"Measurement"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"103622","DOI":"10.1016\/j.autcon.2021.103622","article-title":"Automation for sewer pipe assessment: CCTV video interpretation algorithm and sewer pipe video assessment (SPVA) system development","volume":"125","author":"Yin","year":"2021","journal-title":"Autom. Constr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"104595","DOI":"10.1016\/j.autcon.2022.104595","article-title":"Automatic defogging, deblurring, and real-time segmentation system for sewer pipeline defects","volume":"144","author":"Ma","year":"2022","journal-title":"Autom. Constr."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"101079","DOI":"10.1016\/j.gmod.2020.101079","article-title":"DeepPipes: Learning 3D pipelines reconstruction from point clouds","volume":"111","author":"Cheng","year":"2020","journal-title":"Graph. Model."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4069","DOI":"10.1109\/TIV.2023.3282567","article-title":"HYDRO-3D: Hybrid Object Detection and Tracking for Cooperative Perception Using 3D LiDAR","volume":"8","author":"Meng","year":"2023","journal-title":"IEEE Trans. Intell. Veh."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Pang, G., Wang, N., Fang, H., Liu, H., and Huang, F. (2022). Study of damage quantification of concrete drainage pipes based on point cloud segmentation and reconstruction. 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