Toggle Main Menu Toggle Search

Open Access padlockePrints

Pipeline in-line inspection method, instrumentation and data management

Lookup NU author(s): Professor Gui Yun TianORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2021 by the authors. Licensee MDPI, Basel, Switzerland.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.

Publication metadata

Author(s): Ma Q, Tian G, Zeng Y, Li R, Song H, Wang Z, Gao B, Zeng K

Publication type: Review

Publication status: Published

Journal: Sensors

Year: 2021

Volume: 21

Issue: 11

Online publication date: 03/06/2021

Acceptance date: 24/05/2021

ISSN (electronic): 1424-8220

Publisher: MDPI AG


DOI: 10.3390/s21113862