Výsledky vyhledávání - "Sewer inspection"

Akademický článek

Cost optimization of sewage pipelines inspection

Autor: Mohamed Abdel-Hamid Mohamed, Marwa Adel Ramadan, Karim M. El-Dash

Publikováno v: Ain Shams Engineering Journal, Vol 14, Iss 5, Pp 101960- (2023)

Sewage pipelines are considered to be the invaluable asset in municipalities. Inspection process plays a vital role in operation and maintenance (O&M) strategies applied by the concerned municipalities. Fault inspection and regular maintenance of sew

Externí odkaz: https://doaj.org/article/0ffa2f27314245d5b0d89fcf7c4d4c2f

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Akademický článek

Automatic Detection Method of Sewer Pipe Defects Using Deep Learning Techniques

Autor: Jiawei Zhang, Xiang Liu, Xing Zhang, Zhenghao Xi, Shuohong Wang

Publikováno v: Applied Sciences, Vol 13, Iss 7, p 4589 (2023)

Regular inspection of sewer pipes can detect serious defects in time, which is significant to ensure the healthy operation of sewer systems and urban safety. Currently, the widely used closed-circuit television (CCTV) inspection system relies mainly

Externí odkaz: https://doaj.org/article/ee43d75fd09c4bfda8e8ccb6cbe28e18

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Akademický článek

Design and Implementation of a Video-Frame Localization System for a Drifting Camera-Based Sewer Inspection System

Autor: Yusuke Chikamoto, Yuki Tsutsumi, Hiroaki Sawano, Susumu Ishihara

Publikováno v: Sensors, Vol 23, Iss 2, p 793 (2023)

To reduce the cost of inspecting old sewer pipes, we have been developing a low-cost sewer inspection system that uses drifting wireless cameras to record videos of the interior of a sewer pipe while drifting. The video’s data are transmitted to ac

Externí odkaz: https://doaj.org/article/3470ba606bd74a0a81ea19a88a91d140

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Dissertation/ Thesis

A Decentralized Solution for Sewer Leakage Detection

Autor: Sadeghikhah, Afshin

Undichte Abwassersysteme sind in unserer urbanisierten Welt allgegenwärtig, und aufgrund ihrer versteckten Infrastruktur und der schwierigen Überwachung bleiben ihre Leckagen oft in der Anfangsphase unbemerkt. Trotz der umfangreichen technologische

Externí odkaz: https://tud.qucosa.de/id/qucosa%3A90520
https://tud.qucosa.de/api/qucosa%3A90520/attachment/ATT-0/

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Real world design and implementation of pathfinding sewer inspection robot using a-star algorithm

Autor: Rumaksari, Atyanta, Adri Gabriel Sooai, Gloria Song Abimanyu, Gunawan Dewantoro, Hartanto Kusuma Wardana, Budihardja Murtianta, Lukas Bambang Setyawan

Publikováno v: Jurnal Mantik; Vol. 7 No. 1 (2023): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik); 202-215

This paper presents the design and implementation of a sewer inspection robot that utilizes the A-Star algorithm for pathfinding. The robot is intended to provide a more efficient solution for culvert workers in inspecting sewer pipes, particularly i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=ec830ca20f1b::85da542b5631cdc2b9f1fb20360bab4c
https://iocscience.org/ejournal/index.php/mantik/article/view/3702

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Akademický článek

3D Sensors for Sewer Inspection: A Quantitative Review and Analysis

Autor: Chris H. Bahnsen, Anders S. Johansen, Mark P. Philipsen, Jesper W. Henriksen, Kamal Nasrollahi, Thomas B. Moeslund

Publikováno v: Sensors, Vol 21, Iss 7, p 2553 (2021)

Automating inspection of critical infrastructure such as sewer systems will help utilities optimize maintenance and replacement schedules. The current inspection process consists of manual reviews of video as an operator controls a sewer inspection v

Externí odkaz: https://doaj.org/article/1b855a1a4c9d456e94e85bac70f18ff1

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A Practice Report of Video Processing and a Drifting Camera System for Screening of a Sewer Pipeline

Publikováno v: 情報処理学会論文誌デジタルプラクティス. 3(2):22-31

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=jairo_______::6f1e300c5aeedab37fd95c2a147c3209
http://hdl.handle.net/10297/00028954

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Multi-scale hybrid vision transformer and Sinkhorn tokenizer for sewer defect classification

Autor: Joakim Bruslund Haurum, Meysam Madadi, Sergio Escalera, Thomas B. Moeslund

Publikováno v: Haurum, J B, Madadi, M, Guerrero, S E & Moeslund, T B 2022, ' Multi-scale hybrid vision transformer and Sinkhorn tokenizer for sewer defect classification ', Automation in Construction, vol. 144, 104614 . https://doi.org/10.1016/j.autcon.2022.104614

A crucial part of image classification consists of capturing non-local spatial semantics of image content. This paper describes the multi-scale hybrid vision transformer (MSHViT), an extension of the classical convolutional neural network (CNN) backb

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::698a8c11f40098b4308d0cd4b2a98dde
https://vbn.aau.dk/ws/files/492073391/1_s2.0_S0926580522004848_main.pdf

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