Prediction of Fatigue Crack Propagation in X80 Pipeline Steel Using Acoustic Emission Sensing

作者：Yan Yan, Wei Liu, Yuanhang Gong, Xiaohui Zhang, Ting Shang, Jiaqi Pei, Bin Gao, Xin Li · 发表于：IEEE Sensors Journal · 年份：2025 · DOI：10.1109/JSEN.2024.3521453 · 被引用次数：7

Fatigue cracks in gas pipelines, particularly those constructed from X80 steel, pose significant risks of catastrophic failure if not monitored continuously. This study presents a novel methodology for predicting the fatigue crack propagation rate (FCPR) of X80 pipeline steel by using an acoustic emission (AE) sensing technique. Through a series of three-point bending fatigue tests conducted under varying loading conditions, the influence of the stress ratio and maximum load on the fatigue crack propagation behavior of X80 pipeline steel is investigated. Furthermore, the characteristics of AE signals generated during the stable and rapid crack propagation stages have been analyzed. A new AE feature, related to the average AE amplitude rate, is proposed, demonstrating a stronger linear correlation with the FCPR than traditional AE feature metrics. Based on this newly proposed AE feature, a predictive model for fatigue crack propagation has been developed, which not only accurately identifies the transition from stable to rapid crack propagation but also offers precise real-time predictions of the FCPR, with predictions falling within the 95% confidence interval of measured values. These findings offer a robust framework for real-time structural health monitoring of pipelines, enhancing early intervention strategies and improving safety protocols for critical pipeline infrastructure.