Deadline for manuscript submissions: 30 December 2025
Special Issue Editors
Prof. Jialin Cui Website E-Mail: cuijialin001@hrbeu.edu.cn
Guest Editor
Harbin Engineering of Technology, China
Interests: Structural Health Monitoring (SHM), Damage Identification, Signal Processing, Machine Learning, Non-Destructive Testing
Prof. Jinbo Du Website E-Mail: zju_dujin@zju.edu.cn
Guest Editor
Zhejiang University, China
Interests: Structural Health Monitoring (SHM), Signal Processing, Non-Destructive Testing
Summary
Structural Health Monitoring (SHM) has emerged as a vital component in civil engineering for the long-term safety assessment and performance evaluation of critical infrastructure, including bridges, tunnels, and high-rise structures. This Special Issue highlights recent advancements in SHM techniques, with a particular focus on the application of Acoustic Emission (AE) technology for early-stage damage detection.
As a passive, non-destructive, and real-time monitoring method, AE is capable of capturing transient elastic waves generated by material degradation processes such as crack propagation, corrosion, and fatigue. When integrated with smart sensors, advanced signal processing, and machine learning algorithms, AE systems can significantly enhance the precision, automation, and intelligence of structural diagnostics.
This Special Issue invites high-quality contributions that address novel AE-based SHM methodologies, theoretical modeling of wave propagation, damage localization algorithms, sensor system development, and practical applications in civil infrastructure. Research that demonstrates interdisciplinary innovation and real-world engineering relevance is particularly encouraged. Emphasis will be placed on contributions that align with the journal’s mission to publish original, application-oriented engineering technologies that are both academically rigorous and practically impactful.
Keywords
Structural Health Monitoring
Acoustic Emission
Damage Identification
Smart Sensors
Non-Destructive Evaluation
Signal Processing
Machine Learning
Bridge and Tunnel Engineering
Structural Safety
Civil Infrastructure
Published Papers
