The Applications and Technologies of Structural Health Monitoring in Civil Structures
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 8306
Special Issue Editors
Interests: structural health monitoring; fatigue assessment; system reliable; corrosion-fatigue; bridge engineering
Interests: structural health monitoring; machine vision; shield tunnel; fatigue analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
After nearly three decades of development in China, structural health monitoring technology has found applications in various civil engineering fields such as bridges, tunnels, high-rise buildings, and wind turbines. This has resulted in the accumulation of a vast amount of monitoring data. Establishing a relationship between environmental load and structural performance using these data is crucial. The rapid advancement of artificial intelligence technology has made it possible to fully extract potentially useful information from this data, leading to its widespread use in structural health monitoring. However, while data-driven structural performance analysis can effectively evaluate a structure’s safety state, the lack of structural physical information can limit the model's generalization capabilities and the reliability of its results. Therefore, it is essential to integrate the prior knowledge of structural physical information with data-driven methods. This approach, known as the data–physics joint driven model, is seen as a future development trend.
Under this background, we would like to organize the Special Issue of “The Applications and Technologies of Structural Health Monitoring in Civil Structures” in Applied Sciences to collect new research and contributions in this field. The manuscripts published in this Special Issue are expected to reflect original research and technological development on topics that include, but are not limited to, the following:
- Probabilistic model and simulation for hazard loads;New monitoring and maintenance methods for infrastructures;
- Intelligent operation and maintenance of structures;
- Applications of artificial intelligence (AI) in structural health monitoring;
- Application of digital twin technology in structural health monitoring;
- Traditional and hybrid machine learning methods;
- Big data analysis.
Dr. Yang Ding
Prof. Dr. Xiaowei Ye
Guest Editors
Manuscript Submission Information
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Keywords
- structural health monitoring
- uncertainty analysis
- randomness characterization
- machine learning
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