Guest Editors
Hua-Ping Wang, Lanzhou University, China
E-mail: wanghuaping1128@sina.cn
Jose Campos e Matos, University of Minho, Portugal
E-mail: jmatos@civil.uminho.pt
Summary
Since most important structures have suffered from micro defects after working for a few years, the health monitoring and condition assessment of these established structures is particularly significant. Smart sensing technology by using different kinds of sensors (i.e., optical fiber sensor, piezoelectric sensor, strain gauge), digital image techniques and remote radar has been performed to monitor the real-time deformation, vibration and damage of the structures. Therefore, a great number of sensing data has been collected, and how to interpret the big data and accurately reflect the physical status of the monitored structures has become an important issue. Static and dynamic structural theories have been adopted to deal with the processing of the sensing data. Artificial intelligence (AI) method combined with the signal processing technique has also been used to recognize the health and damage condition of the structures. Cloud computing technique has also been aided to perform the real-time health monitoring of structures.
Thus, the research topic aims to cover original or review articles exploring the innovation in sensing data based structural health monitoring (SHM). The special issue intends to include, but not limited to:
• Smart sensors and structures
• Sensing data based SHM
• Static and dynamic analysis based on sensing data
• Health and damage condition assessment
• Structural parametric reflection based on monitoring technique
• Sensing data motivated model updating and feature recognition
• Big data analysis
• Artificial intelligence-based feature recognition
• Real-time health monitoring based on cloud computing technique
Keywords
Sensing data, Structural health monitoring, Static and dynamic response analysis, Damage identification, Condition assessment
Published Papers