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Data-Centric Structural Health Monitoring by Mohammad Noori,Fuh-Gwo Yuan,Ehsan Noroozinejad Farsangi Pdf
This book introduces the latest developments in data-centric engineering, including different artificial intelligence and machine learning schemes, as well as their wide range of applications for long-term monitoring and health assessment of mechanical, aerospace and complex infrastructure systems. Leading scholars in the field show how these emerging techniques assure the longevity of engineered systems and predict their life cycles.
Structural Health Monitoring Based on Data Science Techniques by Alexandre Cury,Diogo Ribeiro,Filippo Ubertini,Michael D. Todd Pdf
The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of “big data” availability and advanced data science. Such data availability coupled with a wide variety of machine learning and data analytics techniques have led to rapid advancement of how SHM is executed, enabling increased transformation from research to practice. This book intends to present a representative collection of such data science advancements used for SHM applications, providing an important contribution for civil engineers, researchers, and practitioners around the world.
Data Driven Methods for Civil Structural Health Monitoring and Resilience by Mohammad Noori,Carlo Rainieri,Marco Domaneschi,Vasilis Sarhosis Pdf
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.
Data Driven Methods for Civil Structural Health Monitoring and Resilience by Mohammad Noori,Carlo Rainieri,Marco Domaneschi,Vasilis Sarhosis Pdf
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.
Data Driven Methods for Civil Structural Health Monitoring and Resilience by Mohammad Noori,Carlo Rainieri,Marco Domaneschi,Vasilis Sarhosis Pdf
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.
Structural Health Monitoring by Daniel Balageas,Claus-Peter Fritzen,Alfredo Güemes Pdf
This book is organized around the various sensing techniques used to achieve structural health monitoring. Its main focus is on sensors, signal and data reduction methods and inverse techniques, which enable the identification of the physical parameters, affected by the presence of the damage, on which a diagnostic is established. Structural Health Monitoring is not oriented by the type of applications or linked to special classes of problems, but rather presents broader families of techniques: vibration and modal analysis; optical fibre sensing; acousto-ultrasonics, using piezoelectric transducers; and electric and electromagnetic techniques. Each chapter has been written by specialists in the subject area who possess a broad range of practical experience. The book will be accessible to students and those new to the field, but the exhaustive overview of present research and development, as well as the numerous references provided, also make it required reading for experienced researchers and engineers.
Structural Health Monitoring by Time Series Analysis and Statistical Distance Measures by Alireza Entezami Pdf
This book conducts effective research on data-driven Structural Health Monitoring (SHM), and accordingly presents many novel feature extraction methods by time series analysis and signal processing, to extract reliable damage sensitive features from vibration responses. In this regard, some limitations of time series modeling are dealt with. For decision-making, innovative distance-based novelty detection techniques are presented to detect, locate, and quantify different damage scenarios. The performance of the presented methods is demonstrated via laboratory and full-scale structures along with several comparative studies. The main target audience of the book includes scholars, graduate students working on SHM via statistical pattern recognition in terms of feature extraction and classification for damage diagnosis under environmental and operational variations; it would also be beneficial for practicing engineers whose work involves these topics.
Structural Health Monitoring by Charles R. Farrar,Keith Worden Pdf
Written by global leaders and pioneers in the field, this book is a must-have read for researchers, practicing engineers and university faculty working in SHM. Structural Health Monitoring: A Machine Learning Perspective is the first comprehensive book on the general problem of structural health monitoring. The authors, renowned experts in the field, consider structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm, first explaining the paradigm in general terms then explaining the process in detail with further insight provided via numerical and experimental studies of laboratory test specimens and in-situ structures. This paradigm provides a comprehensive framework for developing SHM solutions. Structural Health Monitoring: A Machine Learning Perspective makes extensive use of the authors’ detailed surveys of the technical literature, the experience they have gained from teaching numerous courses on this subject, and the results of performing numerous analytical and experimental structural health monitoring studies. Considers structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm Emphasises an integrated approach to the development of structural health monitoring solutions by coupling the measurement hardware portion of the problem directly with the data interrogation algorithms Benefits from extensive use of the authors’ detailed surveys of 800 papers in the technical literature and the experience they have gained from teaching numerous short courses on this subject.
Civil Structural Health Monitoring by Carlo Rainieri,Giovanni Fabbrocino,Nicola Caterino,Francesca Ceroni,Matilde A. Notarangelo Pdf
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.
Structural Health Monitoring For Advanced Composite Structures by Aliabadi M H Ferri,Sharif Khodaei Zahra Pdf
Structural health monitoring (SHM) is a relatively new and alternative way of non-destructive inspection (NDI). It is the process of implementing a damage detection and characterization strategy for composite structures. The basis of SHM is the application of permanent fixed sensors on a structure, combined with minimum manual intervention to monitor its structural integrity. These sensors detect changes to the material and/or geometric properties of a structural system, including changes to the boundary conditions and system connectivity, which adversely affect the system's performance. This book's primary focus is on the diagnostics element of SHM, namely damage detection in composite structures. The techniques covered include the use of Piezoelectric transducers for active and passive Ultrasonics guided waves and electromechanical impedance measurements, and fiber optic sensors for strain sensing. It also includes numerical modeling of wave propagation in composite structures. Contributed chapters written by leading researchers in the field describe each of these techniques, making it a key text for researchers and NDI practitioners as well as postgraduate students in a number of specialties including materials, aerospace, mechanical and computational engineering. Contents: Damage Detection and Characterization with Piezoelectric Transducers — Active Sensing (Z Sharif Khodaei and M H Aliabadi)Modeling Guided Wave Propagation in Composite Structures Using Local Interaction Simulation Approach (Yanfeng Shen and Carlos E S Cesnik)Design and Development of a Phased Array System for Damage Detection in Structures (Bruno Rocha, Mehmet Yildiz & Afzal Suleman)Degradation Detection in Composite Structures with PZT Transducers (Wiesław M Ostachowicz, Paweł H Malinowski & Tomasz Wandowski)Numerical Modelling of Wave Propagation in Composite Structures (Sourav Banerjee)SHM of Composite Structures by Fibre Optic Sensors (Alfredo Guemes)Impact Detection and Identification with Piezoceramic Sensors — Passive Sensing (Z Sharif Khodaei and M H Aliabadi) Readership: Researchers and NDI practitioners as well as postgraduate students in a number of specialties including materials, aerospace, mechanical and computational engineering. Keywords: Structural Health Modelling;Non-Destrctive Inspection;Dignostic SHM;Aerospace Engineering;Microelectromechanical Systems;Acoustic Emission Monitoring;AccelerometersReview:0
European Workshop on Structural Health Monitoring by Piervincenzo Rizzo,Alberto Milazzo Pdf
This volume gathers the latest advances, innovations, and applications in the field of structural health monitoring (SHM) and more broadly in the fields of smart materials and intelligent systems, as presented by leading international researchers and engineers at the 10th European Workshop on Structural Health Monitoring (EWSHM), held in Palermo, Italy on July 4-7, 2022. The volume covers highly diverse topics, including signal processing, smart sensors, autonomous systems, remote sensing and support, UAV platforms for SHM, Internet of Things, Industry 4.0, and SHM for civil structures and infrastructures. The contributions, which are published after a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaboration among different specialists.
Sensor Networks in Structural Health Monitoring: From Theory to Practice by Eleni Chatzi,Vasilis K. Dertimanis Pdf
The intense development of novel data-driven and hybrid methods for structural health monitoring (SHM) has been demonstrated by field deployments on large-scale systems, including transport, wind energy, and building infrastructure. The actionability of SHM as an essential resource for life-cycle and resilience management is heavily dependent on the advent of low-cost and easily deployable sensors Nonetheless, in optimizing these deployments, a number of open issues remain with respect to the sensing side. These are associated with the type, configuration, and eventual processing of the information acquired from these sensors to deliver continuous behavioral signatures of the monitored structures. This book discusses the latest advances in the field of sensor networks for SHM. The focus lies both in active research on the theoretical foundations of optimally deploying and operating sensor networks and in those technological developments that might designate the next generation of sensing solutions targeted for SHM. The included contributions span the complete SHM information chain, from sensor design to configuration, data interpretation, and triggering of reactive action. The featured papers published in this Special Issue offer an overview of the state of the art and further proceed to introduce novel methods and tools. Particular attention is given to the treatment of uncertainty, which inherently describes the sensed information and the behavior of monitored systems.
Structural Health Monitoring of Aerospace Composites by Victor Giurgiutiu Pdf
Structural Health Monitoring of Aerospace Composite Structures offers a comprehensive review of established and promising technologies under development in the emerging area of structural health monitoring (SHM) of aerospace composite structures. Beginning with a description of the different types of composite damage, which differ fundamentally from the damage states encountered in metallic airframes, the book moves on to describe the SHM methods and sensors currently under consideration before considering application examples related to specific composites, SHM sensors, and detection methods. Expert author Victor Giurgiutiu closes with a valuable discussion of the advantages and limitations of various sensors and methods, helping you to make informed choices in your structure research and development. The first comprehensive review of one of the most ardent research areas in aerospace structures, providing breadth and detail to bring engineers and researchers up to speed on this rapidly developing field Covers the main classes of SHM sensors, including fiber optic sensors, piezoelectric wafer active sensors, electrical properties sensors and conventional resistance strain gauges, and considers their applications and limitation Includes details of active approaches, including acousto-ultrasonics, vibration, frequency transfer function, guided-wave tomography, phased arrays, and electrochemical impedance spectroscopy (ECIS), among other emerging methods
Mechatronics for Cultural Heritage and Civil Engineering by Erika Ottaviano,Assunta Pelliccio,Vincenzo Gattulli Pdf
This book presents recent advances in mechatronic and integrated monitoring and management systems with applications to architectural, archaeology survey, construction management and civil engineering. It consists of 16 chapters authored by recognized experts in a variety of fields including dynamics, signal processing, inverse modeling, robotics and automation, in particular, here applied to design and construction of civil structures and architectural survey, monitoring and maintenance of cultural heritage assets, structures and infrastructure. The book is organized in three main sections: “Robotics and Automation”, “Digital Technologies for Cultural Heritage” and “Civil Structural Health Monitoring”. Topics include image processing for automated visual inspection, fiber optical sensor technology, wireless sensor monitoring, bridge inspection and monitoring of tunnel infrastructures, design tools for construction engineering, smart cities. Direct and inverse modeling of multibody systems and robots contributes to the development of applications for civil engineering and smart cities. Digital technology and mechatronic systems changes the way of looking at restoration of historical and archeological sites, analysis, inspection, visualization, management systems and sensor network for Human-Machine Interfaces (HMI). Combined use of geographical information system (GIS), laser scanner, remote sensing, digital thermography and drones as integrated systems permits to highlight new frontier for building and infrastructure knowledge. The book offers a valuable reference work for scientists, architects, engineers, researchers and practitioners in engineering and architecture since the integrated development of new technologies for the design and management of existing and new infrastructure may produce a new market of services and products for safe and economically optimized infrastructure management. Through the dissemination of advanced research developments in mechatronics and integrated management systems, the book promotes exchanges and collaborations among researchers of different disciplines. The book contributes to further advancements in the rapidly growing field of integration of robotic, automation and information technologies in the area of facilities and infrastructure management and construction processes.
