Innovations in Structural Safety: Advanced Damage Detection and Safety Analysis

Dear Colleagues,

The safety and longevity of hydraulic and civil engineering infrastructures, such as dams, bridges, and slopes, are fundamental to socio-economic stability and public security. However, as global infrastructure enters a phase of large-scale aging, combined with the increasing frequency of extreme climate events and multi-hazard coupling, traditional safety assessment paradigms face unprecedented challenges. Conventional structural health monitoring (SHM) often relies on manual inspections and discrete sensor networks, which lack the spatiotemporal resolution required to capture the evolutionary mechanisms of internal micro-damage or transient responses under complex environmental loads. Furthermore, there remains a critical disconnect between the massive accumulation of monitoring data and the generation of actionable maintenance insights. To bridge this gap and ensure structural integrity throughout the full lifecycle, a paradigm shift from “reactive remediation” to “proactive intelligent O&M” is imperative. This transition demands resilient methodologies capable of fusing heterogeneous data streams to provide precise, real-time assessments of structural performance.

This Special Issue aims to provide a high-level academic platform for the latest breakthroughs in intelligent structural safety assessment, focusing on the deep integration of advanced sensing technologies, artificial intelligence (AI), and structural mechanics. We seek innovative contributions that leverage computer vision, digital twins, unmanned systems (UAVs/ROVs), and advanced data analytics to address critical challenges such as early micro-damage identification and multi-source information fusion. We particularly welcome research that utilizes these advanced technologies to construct precise, real-time, and intelligent safety prevention frameworks. By bridging the gap between theoretical innovation and practical engineering applications, this collection strives to accelerate the transition toward “online perception, intelligent diagnosis, and proactive early warning,” providing a robust scientific foundation for the resilient design and sustainable operation of critical infrastructure systems.

High-quality submissions are invited that address, but are not limited to, the following areas:

• Structural safety monitoring and analysis;
• Structural damage detection and monitoring analysis;
• Structural damage detection and analysis based on image recognition;
• Cross-domain image enhancement techniques based on transfer learning;
• AI-driven methods for structural deformation prediction and analysis;
• Joint data- and mechanism-driven evaluation of structural deformation;
• Monitoring and evaluation analysis of slope deformation;
• Dam safety and stability analysis;
• Research on dynamic analysis models for structural safety;
• Application of UAVs and Underwater Robots (ROV) in structural inspection.

Dr. Chuan Lin
Prof. Dr. Fei Kang
Dr. Qiubing Ren
Guest Editors

Manuscript Submission Information

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• computer vision
• digital twin
• structural health monitoring
• data-driven
• UAV imagery
• intelligent diagnosis
• deformation prediction
• safety assessment
• artificial intelligence model