Structural health monitoring (SHM) is a multidisciplinary problem that involves modeling and simulation, damage detection, information management and prognosis. This book is designed to provide readers with a clear idea of all the challenges that need to be tackled before an SHM system can be implemented in real structures.
Structural health monitoring (SHM) is a multidisciplinary problem that involves modeling and simulation, damage detection, information management and prognosis. This book is designed to provide readers with a clear idea of all the challenges that need to be tackled before an SHM system can be implemented in real structures.
Dr. Aditi Chattopadhyay is a Professor of Mechanical and Aerospace Engineering in the School for Engineering of Matter, Transport and Energy and Director of the Adaptive, Intelligent Materials and Systems Center (AIMS) at Arizona State University (ASU). Dr. Mark Seaver is a Research Physicist (retired) affiliated with the Naval Research Laboratory, Washington, DC.
Inhaltsangabe
Introduction. Need for Condition Based Monitoring. What is Structural Health Monitoring? Advantages of SHM. Multidisciplinary Nature of SHM. Overview of Existing SHM and NOT Technologies. SHM Concepts and Principles. Modeling Needs. Modeling Needs. Multiscale Damage Models. Stochastic Modeling. Virtual Sensing. Structural Modeling for Life Estimation. Sensors for SHM. Sensor Selection Considerations. Passive vs. Active Sensing. Survey of Wave Based Sensors for Usage/Condition Monitoring. Survey of Strain Based Sensors for Usage/Condition Monitoring. Sensor Networks and Wireless Sensing. Implementation Considerations. Data Collection and Information Management. Measurement Needs. Data Acquisition. Data Preprocessing and Storage. Feature Extraction. Damage Assessment. Damage Detection. Damage Localization. Damage Quantification. Structural Life Estimation. Physics Based Methods. Data Driven Methods. Hybrid Approaches. Case Study 1: Aerospace Application. Case Study 2: Naval Application. Case Study 3: Civil Application.
Introduction. Need for Condition Based Monitoring. What is Structural Health Monitoring? Advantages of SHM. Multidisciplinary Nature of SHM. Overview of Existing SHM and NOT Technologies. SHM Concepts and Principles. Modeling Needs. Modeling Needs. Multiscale Damage Models. Stochastic Modeling. Virtual Sensing. Structural Modeling for Life Estimation. Sensors for SHM. Sensor Selection Considerations. Passive vs. Active Sensing. Survey of Wave Based Sensors for Usage/Condition Monitoring. Survey of Strain Based Sensors for Usage/Condition Monitoring. Sensor Networks and Wireless Sensing. Implementation Considerations. Data Collection and Information Management. Measurement Needs. Data Acquisition. Data Preprocessing and Storage. Feature Extraction. Damage Assessment. Damage Detection. Damage Localization. Damage Quantification. Structural Life Estimation. Physics Based Methods. Data Driven Methods. Hybrid Approaches. Case Study 1: Aerospace Application. Case Study 2: Naval Application. Case Study 3: Civil Application.
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