1st Edition
Structural Health Monitoring Using Emerging Signal Processing Approaches with Artificial Intelligence Algorithms
Structural health monitoring is a powerful tool across civil, mechanical, automotive, and aerospace engineering, allowing the assessment and measurement of physical parameters in real time. Processing changes in the vibration signals of a dynamic system can detect, locate, and quantify any damage existing in the system. This book presents a comprehensive state-of-the-art review of the applications in time, frequency, and time-frequency domains of signal processing techniques for damage perception, localization, and quantification in various structural systems.
Experimental investigations are illustrated, including the development of a set of damage indices based on the signal features extracted through various signal processing techniques to evaluate sensitivity in damage identification. Chapters summarize the application of the Hilbert–Huang transform based on three decomposition methods of empirical mode decomposition, ensemble empirical mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise. Also assessed are the performance and sensitivity of different approaches, including multiple signal classification and empirical wavelet transform techniques in damage detection and quantification. Artificial Neural Networks for automated damage identification are introduced.
This book suits students, engineers, and researchers who are investigating structural health monitoring, signal processing, and damage identification of structures.
1. Introduction.
2. Methodology and Approaches.
3. Implementation of the Proposed Approaches in Structural Damage Detection and Quantification.
4. Implementation of the Proposed Approaches in Structural Damage Localization.
5. Experimental Verification of the Proposed Artificial Neural Network Aided Approaches in Structural Damage Identification.
6. Conclusions.
Biography
Chunwei Zhang is a Distinguished Professor and Du Xing Endowed Scholar at South China University of Technology. He is the Founding Director of the Multidisciplinary Center for Infrastructure Engineering (MCIE) at Shenyang University of Technology, and the Founding Director of the Structural Vibration Control (SVC) Group at Qingdao University of Technology, China. His research achievements and worldwide impact have been recognized by the international academic community and his inventions implemented in practice, such as in the active control system for the Canton tower. He is also a commended author of several CRC Press books and proceedings.
Asma A. Mousavi is a postdoctoral researcher at South China University of Technology.
