Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications (Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems)

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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications (Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems)

Noori, Mohammad (EDT)/ Rainieri, Carlo (EDT)/ Domaneschi, Marco (EDT)

ウェブストア価格 ¥29,102（本体¥26,457）
CRC Press（2023/10発売）
外貨定価 US$ 130.00
ポイント 264pt

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製本 Hardcover:ハードカバー版／ページ数 342 p.
言語 ENG
商品コード 9781032308371
DDC分類 624.1710285

Full Description

Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers.

1. Structural Resilience through SHM: A Critical Review. 2. Differential Evolution Algorithm: An analysis of more than two decades of application in structural damage detection (2001-2022). 3. Fatigue Assessment and SHM of Steel Truss Bridges. 4. Sensor-Based Structural Assessment of Ageing Bridges Sensor-Based Assessment . 5. Pile Integrity Assessment through A Staged Data Interpretation Framework. 6. Data-Centric Monitoring of Wind Farms: Combining Sources of Information. 7. From Structural Health Monitoring to Finite Element Modelling of Heritage Structures: The Medieval Towers of Lucca. 8. Development of adaptive LQG controller for Structural Control using Particle Swarm Optimization. 9. Application of AI Tools in Creating Datasets from A Real Data Component for Structural Health Monitoring. 10. Ambient Vibration Prediction of a Cable-Stayed Bridge by Artificial Neural Network. 11. Modeling Uncertainties by Data-Driven Bayesian Updating for Structural and Damage Detection. 12. Image Processing for SHM: The resilience of computer vision-based monitoring systems and their measurement. 13. Automatic SHM of road surfaces using Artificial Intelligence and Deep Learning. 14. Computer Vision-based Intelligent Disaster Mitigation from Two Aspects of Structural System Identification and Local Damage Detection.