Defect detection in pipelines via guided wave-based time-frequency-domain reflectometry

Su Sik Bang, Yeong Ho Lee, Yong June Shin

Research output: Contribution to journalArticlepeer-review

Abstract

In order to improve the performance of the conventional guided wave testing (GWT) with a low sensitivity on damage in pipelines, a new GWT based on time-frequency-domain reflectometry (TFDR) is proposed. TFDR using electromagnetic signals is a diagnostic technique for electrical cables, and the signal is analyzed in both time and frequency domains to enhance the resolution of faults in the electrical cables. Since it is impossible to directly apply the TFDR methodology for electrical cables to the pipelines, this article presents new TFDR methodologies suitable for the ultrasonic characteristics of the pipelines. The proposed technique is demonstrated by experiments using a real-world pipeline. The analysis of the experimental results depending on the changes in the defect size and internal material of the pipeline is provided, and the performance of the proposed technique is confirmed by the experiments.

Original languageEnglish
Article number9340006
JournalIEEE Transactions on Instrumentation and Measurement
Volume70
DOIs
Publication statusPublished - 2021

Bibliographical note

Funding Information:
Manuscript received October 31, 2020; revised December 14, 2020; accepted January 6, 2021. Date of publication January 28, 2021; date of current version February 17, 2021. This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science, ICT and Future Planning under Grant NRF-2020R1A2B5B03001692 and in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under Grant NRF-2020R1A6A3A13075204. The Associate Editor coordinating the review process for this article was Dr. Chao Tan. (Corresponding author: Yong-June Shin.) The authors are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea (e-mail: yongjune@yonsei.ac.kr). Digital Object Identifier 10.1109/TIM.2021.3055277

Publisher Copyright:
© 1963-2012 IEEE.

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Defect detection in pipelines via guided wave-based time-frequency-domain reflectometry'. Together they form a unique fingerprint.

Cite this