Pipeline In-Line Inspection Method, Instrumentation and Data Management

无损检测 漏磁 管道(软件) 诚信管理 管道运输 超声波检测 工程类 涡流 仪表(计算机编程) 可靠性工程 机器人 超声波传感器 计算机科学 机械工程 电气工程 声学 人工智能 磁铁 放射科 物理 操作系统 医学
作者
Qiuping Ma,Gui Yun Tian,Yanli Zeng,Rui Li,Huadong Song,Zhen Wang,Bin Gao,Kun Zeng
出处
期刊:Sensors [Multidisciplinary Digital Publishing Institute]
卷期号:21 (11): 3862-3862 被引量:126
标识
DOI:10.3390/s21113862
摘要

Pipelines play an important role in the national/international transportation of natural gas, petroleum products, and other energy resources. Pipelines are set up in different environments and consequently suffer various damage challenges, such as environmental electrochemical reaction, welding defects, and external force damage, etc. Defects like metal loss, pitting, and cracks destroy the pipeline’s integrity and cause serious safety issues. This should be prevented before it occurs to ensure the safe operation of the pipeline. In recent years, different non-destructive testing (NDT) methods have been developed for in-line pipeline inspection. These are magnetic flux leakage (MFL) testing, ultrasonic testing (UT), electromagnetic acoustic technology (EMAT), eddy current testing (EC). Single modality or different kinds of integrated NDT system named Pipeline Inspection Gauge (PIG) or un-piggable robotic inspection systems have been developed. Moreover, data management in conjunction with historic data for condition-based pipeline maintenance becomes important as well. In this study, various inspection methods in association with non-destructive testing are investigated. The state of the art of PIGs, un-piggable robots, as well as instrumental applications, are systematically compared. Furthermore, data models and management are utilized for defect quantification, classification, failure prediction and maintenance. Finally, the challenges, problems, and development trends of pipeline inspection as well as data management are derived and discussed.
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