Xu, Z., Sampath, S., Wang, X., Dong, H., Liu, Y., Wang, Y., Zhang, H., Zhang, L., Tham, J., Liu, Z., & Hu, D. J. J. (2026). Review on structural health monitoring of pipeline: from perspective on acoustic based crack detection. Measurement, 263, 120075. https://doi.org/10.1016/j.measurement.2025.120075
Abstract:
The detection of cracking in pipelines remains a critical challenge in structural health monitoring (SHM). Acoustic emission (AE) sensors are widely adopted due to their affordability and effectiveness in detecting crack initiation and propagation and offer real-time data on key signal parameters. Meanwhile, advancements in numerical modeling, including machine learning and artificial intelligence, provide powerful tools for analyzing AE data, predicting failure, and guiding maintenance. This paper highlights the current state of AE-based pipeline crack detection, evaluates the strengths and limitations of key technologies, and explores future directions toward hybrid SHM systems that integrate conventional sensors, fiber optics, and intelligent algorithms.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the National Research Foundation, Singapore - Low Carbon Energy Research Phase 2 Programme HETFI Directed Hydrogen Programme
Grant Reference no. : Grant No: U2307D4002