Damage Detection And Structural Health Monitoring Of Concrete And Masonry Structures
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Damage Detection and Structural Health Monitoring of Concrete and Masonry Structures
This book offers the use of artificial intelligence, image processing, model analysis, laser scanners, shearography, drones, contourlet, wavelet, signal processing techniques and other SHM techniques to detect the damages in the concrete as well as masonry structures. Corrosion is one major factor that causes reinforced concrete structures to deteriorate over time. However, the degrading process is not evenly distributed throughout the structure. The damage can be detected timely and the structure's degradation model can be updated with the help of proper monitoring and inspection techniques. The damages in the masonry structures may happen due to moisture ingress, cracking, mortar failure, settlement and spalling, etc. Structure health monitoring (SHM) may assist in understanding the structures deterioration mechanisms and reducing the ongoing deterioration in a scientific manner. A complete detail of both the traditional and cutting-edge approaches used in the SHM process is described in this book. The latest non-destructive techniques and semi-destructive techniques shall also be discussed in this book. This book aids academics and industry professionals with recent developments in SHM techniques. Additionally, it encourages researchers in coming up with creation of newer applications in structural engineering.
Structural Health Monitoring (SHM) of Civil Structures
This book is a printed edition of the Special Issue "Structural Health Monitoring (SHM) of Civil Structures" that was published in Applied Sciences
Civil Structural Health Monitoring
This volume gathers the latest advances and innovations in the field of structural health monitoring, as presented at the 8th Civil Structural Health Monitoring Workshop (CSHM-8), held on March 31-April 2, 2021. It discusses emerging challenges in civil SHM and more broadly in the fields of smart materials and intelligent systems for civil engineering applications. The contributions cover a diverse range of topics, including applications of SHM to civil structures and infrastructures, innovative sensing solutions for SHM, data-driven damage detection techniques, nonlinear systems and analysis techniques, influence of environmental and operational conditions, aging structures and infrastructures in hazardous environments, and SHM in earthquake prone regions. Selected by means of a rigorous peer-review process, they will spur novel research directions and foster future multidisciplinary collaborations.