Active and Passive Technologies for Long-Term Structural Health Monitoring and Non-Destructive Testing

Submission Deadline: 31 March 2027 View: 20 Submit to Special Issue

Guest Editor(s)

Assoc. Prof. Kai Tao

Email: kai.tao@njupt.edu.cn

Affiliation: College of Automation, Nanjing University of Posts and Telecommunications, Nanjing, China

Homepage:

Research Interests: structural health monitoring, non-destructive testing

Assoc. Prof. Qiao Bao

Email: baoqiao@njupt.edu.cn

Affiliation: College of Automation, Nanjing University of Posts and Telecommunications, Nanjing, China

Homepage:

Research Interests: structural health monitoring, array signal processing

Summary

Modern engineering structures, including aerospace systems, civil infrastructure, and mechanical equipment, are subject to progressive degradation due to environmental factors, fatigue, and operational loads. To ensure safety and extend service life, reliable methodologies for long-term Structural Health Monitoring (SHM) and Non-Destructive Testing (NDT) are essential.

This Special Issue focuses on the development and application of both active and passive monitoring technologies. Active technologies, such as ultrasonic guided waves, sonar, and active thermography, utilize external excitation to interrogate structures and identify localized damage. Passive technologies, such as acoustic emission (AE), microseismic monitoring, vibration analysis, and strain sensing, rely on the structure operational responses or spontaneous energy releases to detect damage initiation and propagation. Both paradigms play critical, distinct roles in evaluating structural integrity across various engineering fields.

We invite high-quality original research and review articles addressing theoretical, numerical, and experimental advancements in either active or passive monitoring techniques.

Topics of interest include, but are not limited to:
· Active monitoring techniques using ultrasonic waves, guided waves, and sonar.
· Passive monitoring techniques based on acoustic emission, microseismic, and vibration analysis.
· Sensor development, optimization, and network deployment for active or passive sensing.
· Signal processing, feature extraction, and noise reduction algorithms for SHM/NDT data.
· Data-driven, machine learning, and physics-informed models for active or passive damage identification.
· Long-term health monitoring of civil infrastructure (bridges, tunnels, dams).
· Online condition monitoring and diagnostics for mechanical and aerospace structures.
· Advanced instrumentation and hardware implementation for field-scale active/passive testing.
· Analytical and numerical modeling of wave propagation and acoustic source mechanisms.

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