Intelligent Structural Health Monitoring for Modern Industrial and Civil Assets
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (25 July 2023) | Viewed by 12738
Special Issue Editors
Interests: structural health monitoring; smart structures; structural dynamics simulation; intelligent nondestructive testing; automatic instrumentation
Interests: signal processing; condition monitoring; data-driven diagnosis
Interests: structural health monitoring and performance evaluation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Modern industrial and civil structure systems apply diverse functional structures to support normal operation. However, the harsh working environments and long-term service of industrial and civil assets make structures prone to defects, such as cracks and corrosion. The failure of different components has been reported, and these failures have resulted in serious consequences to the economy and society. Intelligent structural health monitoring will be beneficial for the early detection of defects, allowing predictive maintenance to be conducted. Nowadays, advanced sensors and artificial intelligence have progressed rapidly. Scientists can use sensor techniques, signal processing methods, and machine learning tools to realize the monitoring, detection, prognostics, diagnosis, and management of the health status of different structures in industrial and civil assets.
This Special Issue aims to present the current achievements and latest developments made by researchers and industrial and civil engineers in intelligent structural health monitoring for modern industrial and civil assets.
Topics include but are not limited to:
- Advanced sensors for structural health monitoring;
- Multi-sensor information fusion techniques;
- Failure detection and diagnosis of industrial machinery;
- Defect detection of electrical devices;
- Damage detection and early warnings of structural anomalies in bridges;
- Structural inspection and analysis of buildings and bridges;
- Advanced feature extraction methods for industrial inspection;
- Artificial Intelligence algorithms in prognostics and health management;
- Condition monitoring and intelligent fault diagnosis;
- Deep learning algorithms for equipment used in environmental sensing applications.
Dr. Xiaobin Hong
Dr. Dingcheng Zhang
Dr. Donghui Yang
Dr. Zhe Wang
Guest Editors
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Keywords
- monitoring sensors
- structural health monitoring
- industrial equipment
- bridge structures
- artificial intelligence
- signal processing
- condition monitoring
- prognostics and diagnosis
- damage detection and early warning
- performance evaluation
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