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Recent Developments in Structural Health Monitoring and Assessment - Opportunities and Challenges, Achintya Haldar, Abdullah Al-Hussein


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Автор: Achintya Haldar, Abdullah Al-Hussein
Название:  Recent Developments in Structural Health Monitoring and Assessment - Opportunities and Challenges
ISBN: 9789811243004
Издательство: World Scientific Publishing
Издательство: World Scientific Publishing Company
Классификация:
ISBN-10: 981124300X
Обложка/Формат: Hardback
Страницы: 448
Вес: 0.77 кг.
Дата издания: 22.02.2022
Серия: Engineering
Язык: English
Размер: 158 x 236 x 16
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Structural engineering, TECHNOLOGY & ENGINEERING / Civil / Bridges,TECHNOLOGY & ENGINEERING / Construction / General,TECHNOLOGY & ENGINEERING / Structural
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Поставляется из: США
Описание:

This is a follow up to Health Assessment of Engineered Structures. It incorporates the most recent developments in health assessment and monitoring of infrastructures covering several advanced conceptual frameworks, different types of sensors, and application potentials. Opportunities and challenges in theoretical, numerical, and experimental investigations generally overlooked in the profession are discussed. Also included are various types of Bayesian filtering concepts improving the commonly used techniques.


Showcasing a multi-faceted, technology-based development in health assessment of infrastructures, several new approaches for health assessment are presented to assess the health of masonry structures, riveted steel railway bridges, and more, such as the use of:

  • Modified Social Group Optimization (MSGO) - a human-based meta-heuristic optimization technique,
  • autonomous crack detection approach using Artificial Intelligence,
  • Augmented Reality (AR) - a digital interface that combines interactive holographic components with the real-world,
  • vision-based noncontact and targetless vibration sensors, as well as
  • intelligent use of smartphone-based health assessment.





Computational Techniques for Structural Health Monitoring

Автор: Srinivasan Gopalakrishnan; Massimo Ruzzene; Sathya
Название: Computational Techniques for Structural Health Monitoring
ISBN: 1447126858 ISBN-13(EAN): 9781447126850
Издательство: Springer
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Цена: 22201.00 р.
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Описание: This one-volume, in-depth introduction to the computational methodologies available for rapid detection of flaws in structures covers techniques, algorithms and results in a way that facilitates their direct application, and includes a number of case studies.

Structural Health Monitoring (SHM) in Aerospace Structures

Автор: Fuh-Gwo Yuan
Название: Structural Health Monitoring (SHM) in Aerospace Structures
ISBN: 0081001487 ISBN-13(EAN): 9780081001486
Издательство: Elsevier Science
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Цена: 33518.00 р.
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Описание: "

Structural Health Monitoring (SHM) in Aerospace Structures "provides readers with the spectacular progress that has taken place over the last twenty years with respect to the area of Structural Health Monitoring (SHM). The widespread adoption of SHM could both significantly improve safety and reduce maintenance and repair expenses that are estimated to be about a quarter of an aircraft fleet s operating costs.

The SHM field encompasses transdisciplinary areas, including smart materials, sensors and actuators, damage diagnosis and prognosis, signal and image processing algorithms, wireless intelligent sensing, data fusion, and energy harvesting. This book focuses on how SHM techniques are applied to aircraft structures with particular emphasis on composite materials, and is divided into four main parts.

Part One provides an overview of SHM technologies for damage detection, diagnosis, and prognosis in aerospace structures. Part Two moves on to analyze smart materials for SHM in aerospace structures, such as piezoelectric materials, optical fibers, and flexoelectricity. In addition, this also includes two vibration-based energy harvesting techniques for powering wireless sensors based on piezoelectric electromechanical coupling and diamagnetic levitation. Part Three explores innovative SHM technologies for damage diagnosis in aerospace structures. Chapters within this section include sparse array imaging techniques and phase array techniques for damage detection. The final section of the volume details innovative SHM technologies for damage prognosis in aerospace structures.

This book serves as a key reference for researchers working within this industry, academic, and government research agencies developing new systems for the SHM of aerospace structures and materials scientists.
Provides key information on the potential of SHM in reducing maintenance and repair costsAnalyzes current SHM technologies and sensing systems, highlighting the innovation in each areaEncompasses chapters on smart materials such as electroactive polymers and optical fibers"

Computer vision for structural dynamics and health monitoring

Автор: Feng, Dongming Feng, Maria Q.
Название: Computer vision for structural dynamics and health monitoring
ISBN: 1119566584 ISBN-13(EAN): 9781119566588
Издательство: Wiley
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Цена: 17733.00 р.
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Описание: Provides comprehensive coverage of theory and hands-on implementation of computer vision-based sensors for structural health monitoring This book is the first to fill the gap between scientific research of computer vision and its practical applications for structural health monitoring (SHM). It provides a complete, state-of-the-art review of the collective experience that the SHM community has gained in recent years. It also extensively explores the potentials of the vision sensor as a fast and cost-effective tool for solving SHM problems based on both time and frequency domain analytics, broadening the application of emerging computer vision sensor technology in not only scientific research but also engineering practice.

Computer Vision for Structural Dynamics and Health Monitoring presents fundamental knowledge, important issues, and practical techniques critical to successful development of vision-based sensors in detail, including robustness of template matching techniques for tracking targets; coordinate conversion methods for determining calibration factors to convert image pixel displacements to physical displacements; sensing by tracking artificial targets vs. natural targets; measurements in real time vs. by post-processing; and field measurement error sources and mitigation methods.

The book also features a wide range of tests conducted in both controlled laboratory and complex field environments in order to evaluate the sensor accuracy and demonstrate the unique features and merits of computer vision-based structural displacement measurement. Offers comprehensive understanding of the principles and applications of computer vision for structural dynamics and health monitoringHelps broaden the application of the emerging computer vision sensor technology from scientific research to engineering practice such as field condition assessment of civil engineering structures and infrastructure systemsIncludes a wide range of laboratory and field testing examples, as well as practical techniques for field applicationProvides MATLAB code for most of the issues discussed including that of image processing, structural dynamics, and SHM applications Computer Vision for Structural Dynamics and Health Monitoring is ideal for graduate students, researchers, and practicing engineers who are interested in learning about this emerging sensor technology and advancing their applications in SHM and other engineering problems. It will also benefit those in civil and aerospace engineering, energy, and computer science.



Structural Health Monitoring Using Genetic Fuzzy Systems

Автор: Prashant M. Pawar; Ranjan Ganguli
Название: Structural Health Monitoring Using Genetic Fuzzy Systems
ISBN: 1447159683 ISBN-13(EAN): 9781447159681
Издательство: Springer
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Цена: 15672.00 р.
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Описание: The high profile of structural health monitoring (SHM) will add urgency to this detailed treatment of intelligent SHM development and implementation via the evolutionary system, which uses a genetic algorithm to automate the development of the fuzzy system.


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