Detection and quantitative assessment of corrosion on pipelines through image analysis

被引:43
作者
Bondada, Venkatasainath [1 ]
Pratihar, Dilip Kumar [1 ]
Kumar, Cheruvu Siva [1 ]
机构
[1] Indian Inst Technol Kharagpur, Dept Mech Engn, Kharagpur 721302, W Bengal, India
来源
INTERNATIONAL CONFERENCE ON ROBOTICS AND SMART MANUFACTURING (ROSMA2018) | 2018年 / 133卷
关键词
Corrosion; Quantitative assessment; Image processing; Clustering;
D O I
10.1016/j.procs.2018.07.115
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Pipeline is one of the safest and most reliable ways of hydrocarbon transportation. With a huge volume of process fluids (hazardous, flammable, corrosive, toxic) being handled, the integrity of pipelines is of the utmost importance to ensure safety of plant, people and environment. Corrosion on the external or internal surfaces of in-service pipes reduces the integrity of the pipeline system and potentially reduces the service life of the pipes. In order to automate inspection of pipelines over long ranges, anew methodology has been proposed using machine vision concepts. Corrosion is identified and the damage due to it has been quantified, which will help the management in maintenance of pipeline integrity to prioritize their remedial measures. (C) 2018 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:804 / 811
页数:8
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