Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Automation for sewer pipe assessment: CCTV video interpretation algorithm and sewer pipe video assessment (SPVA) system development
Abstract This research aims at improving the automation of the sewer pipe assessment process, specifically in terms of the development of a closed-circuit television (CCTV) video interpretation algorithm and sewer pipe video assessment (SPVA) system. A novel video interpretation algorithm for sewer pipes (VIASP) is proposed to use the labeled video (which is labeled by an automated defect detector) as the input in order to extract the useful information from the video, with the final output being the sewer pipe assessment report in textual format. To develop the VIASP, an optimization algorithm using simulated annealing (SA) is employed to determine the optimal human-defined parameters for the VIASP. A prototype of the SPVA system is developed to show how the developed automation techniques can fit into the daily workflow of sewer pipe assessment work. The effectiveness of the proposed method is validated in a case study.
Highlights Pipe information in the CCTV videos is translated to textual information directly. A video interpretation algorithm is proposed to process information in video frames. The video interpretation algorithm is featured by defect frame cluster (DFC). A prototype of the SPVA system is developed to show the practicality of the system.
Automation for sewer pipe assessment: CCTV video interpretation algorithm and sewer pipe video assessment (SPVA) system development
Abstract This research aims at improving the automation of the sewer pipe assessment process, specifically in terms of the development of a closed-circuit television (CCTV) video interpretation algorithm and sewer pipe video assessment (SPVA) system. A novel video interpretation algorithm for sewer pipes (VIASP) is proposed to use the labeled video (which is labeled by an automated defect detector) as the input in order to extract the useful information from the video, with the final output being the sewer pipe assessment report in textual format. To develop the VIASP, an optimization algorithm using simulated annealing (SA) is employed to determine the optimal human-defined parameters for the VIASP. A prototype of the SPVA system is developed to show how the developed automation techniques can fit into the daily workflow of sewer pipe assessment work. The effectiveness of the proposed method is validated in a case study.
Highlights Pipe information in the CCTV videos is translated to textual information directly. A video interpretation algorithm is proposed to process information in video frames. The video interpretation algorithm is featured by defect frame cluster (DFC). A prototype of the SPVA system is developed to show the practicality of the system.
Automation for sewer pipe assessment: CCTV video interpretation algorithm and sewer pipe video assessment (SPVA) system development
Yin, Xianfei (Autor:in) / Ma, Tianxin (Autor:in) / Bouferguene, Ahmed (Autor:in) / Al-Hussein, Mohamed (Autor:in)
05.02.2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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