Automation for sewer pipe assessment: CCTV video interpretation algorithm and sewer pipe video assessment (SPVA) system development

被引：26

作者：

Yin, Xianfei ^{[1
]}

Ma, Tianxin ^{[2
]}

Bouferguene, Ahmed ^{[3
]}

Al-Hussein, Mohamed ^{[4
]}

机构：

[1] Univ Twente, Dept Construct Management & Engn, Enschede, Netherlands

[2] Univ Alberta, Dept Comp Sci, Edmonton, AB, Canada

[3] Univ Alberta, Campus St Jean, Edmonton, AB, Canada

[4] Univ Alberta, Dept Civil & Environm Engn, Edmonton, AB, Canada

来源：

AUTOMATION IN CONSTRUCTION | 2021年 / 125卷

基金：

中国国家自然科学基金; 加拿大自然科学与工程研究理事会;

关键词：

Sewer pipe; CCTV; Assessment; Maintenance; Video interpretation; Automation; DEFECTS; OPTIMIZATION; NETWORKS; IMAGES;

D O I：

10.1016/j.autcon.2021.103622

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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.

引用

页数：15

共 29 条

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