Structural Health Monitoring by Time Series Analysis and Statistical Distance Measures
Structural Health Monitoring by Time Series Analysis and Statistical Distance Measures

Author: Alireza Entezami

Publisher: Springer Nature

Published: 2021-02-01

Total Pages: 145

ISBN-13: 3030662594

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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 Time Series Analysis and Statistical Distance Measures
Structural Health Monitoring by Time Series Analysis and Statistical Distance Measures

Author: Alireza Entezami

Publisher: Springer

Published: 2021-02-02

Total Pages: 136

ISBN-13: 9783030662585

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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.

Long-term Structural Health Monitoring by Remote Sensing and Advanced Machine Learning
Long-term Structural Health Monitoring by Remote Sensing and Advanced Machine Learning

Author: ALIREZA. BEHKAMAL ENTEZAMI (BAHAREH. DE MICHELE, CARLO.)

Publisher: Springer Nature

Published: 2024

Total Pages: 123

ISBN-13: 3031539958

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This book offers an in-depth investigation into the complexities of long-term structural health monitoring (SHM) in civil structures, specifically focusing on the challenges posed by small data and environmental and operational changes (EOCs). Traditional contact-based sensor networks in SHM produce large amounts of data, complicating big data management. In contrast, synthetic aperture radar (SAR)-aided SHM often faces challenges with small datasets and limited displacement data. Additionally, EOCs can mimic the structural damage, resulting in false errors that can critically affect economic and safety issues. Addressing these challenges, this book introduces seven advanced unsupervised learning methods for SHM, combining AI, data sampling, and statistical analysis. These include techniques for managing datasets and addressing EOCs. Methods range from nearest neighbor searching and Hamiltonian Monte Carlo sampling to innovative offline and online learning frameworks, focusing on data augmentation and normalization. Key approaches involve deep autoencoders for data processing and novel algorithms for damage detection. Validated using simulated data from the I-40 Bridge, USA, and real-world data from the Tadcaster Bridge, UK, these methods show promise in addressing SAR-aided SHM challenges, offering practical tools for real-world applications. The book, thereby, presents a comprehensive suite of innovative strategies to advance the field of SHM.

Real-Time Structural Health Monitoring of Vibrating Systems
Real-Time Structural Health Monitoring of Vibrating Systems

Author: Basuraj Bhowmik

Publisher: CRC Press

Published: 2022-09-22

Total Pages: 238

ISBN-13: 1000707156

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Targeted at researchers and practitioners in the field of science and engineering, the book provides an introduction to real time structural health monitoring. Most work to date is based on algorithms that require windowing of the accumulated data, this work presents a coherent transition from the traditional batch mode practice to a recently developed array of recursive approaches. The book mainly focuses on the theoretical development and engineering applications of algorithms that are based on first order perturbation (FOP) techniques. The development of real time algorithms aimed at identifying the structural systems and the inflicted damage, online, through theoretical approaches paves the way for an in-depth understanding of the discussed topics. It then continues to demonstrate the solution to a class of inverse dynamic problems through numerically simulated systems. Extensive theoretical derivations supported by mathematical formulations, pivoted around the simple concepts of eigenspace updates, forms the key cornerstone of the book. The output response streaming in real time from multi degree of freedom systems provide key information about the system’s health that is subsequently utilized to identify the modal parameters and the damage, in real time. Damage indicators connotative of the nature, instant and location of damage, identified in a single framework are developed in the light of real time damage case studies. Backed by a comprehensive assortment of experimental test-beds, this book includes demonstrations to emulate real life damage scenarios under controlled laboratory conditions. Applicability of the proposed recursive methods towards practical problems demonstrate their robustness as viable candidates for real time structural health monitoring.

European Workshop on Structural Health Monitoring
European Workshop on Structural Health Monitoring

Author: Piervincenzo Rizzo

Publisher: Springer Nature

Published: 2021-01-08

Total Pages: 847

ISBN-13: 3030649083

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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. 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. The contents of this volume reflect the outcomes of the activities of EWSHM (European Workshop on Structural Health Monitoring) in 2020.

Structural Health Monitoring Based on Data Science Techniques
Structural Health Monitoring Based on Data Science Techniques

Author: Alexandre Cury

Publisher: Springer Nature

Published: 2021-10-23

Total Pages: 490

ISBN-13: 3030817164

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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.

Structural Sensing, Health Monitoring, and Performance Evaluation
Structural Sensing, Health Monitoring, and Performance Evaluation

Author: D. Huston

Publisher: CRC Press

Published: 2010-09-21

Total Pages: 664

ISBN-13: 1420012355

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Structural health monitoring (SHM) uses one or more in situ sensing systems placed in or around a structure, providing real-time evaluation of its performance and ultimately preventing structural failure. Although most commonly used in civil engineering, such as in roads, bridges, and dams, SHM is now finding applications in other engineering envir

Intelligent Sensor Networks
Intelligent Sensor Networks

Author: Fei Hu

Publisher: CRC Press

Published: 2012-12-15

Total Pages: 676

ISBN-13: 1439892814

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Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, including compressive sensing and sampling, distributed signal processing, and intelligent signal learning. Presenting recent research results of world-renowned sensing experts, the book is organized into three parts: Machine Learning—describes the application of machine learning and other AI principles in sensor network intelligence—covering smart sensor/transducer architecture and data representation for intelligent sensors Signal Processing—considers the optimization of sensor network performance based on digital signal processing techniques—including cross-layer integration of routing and application-specific signal processing as well as on-board image processing in wireless multimedia sensor networks for intelligent transportation systems Networking—focuses on network protocol design in order to achieve an intelligent sensor networking—covering energy-efficient opportunistic routing protocols for sensor networking and multi-agent-driven wireless sensor cooperation Maintaining a focus on "intelligent" designs, the book details signal processing principles in sensor networks. It elaborates on critical platforms for intelligent sensor networks and illustrates key applications—including target tracking, object identification, and structural health monitoring. It also includes a paradigm for validating the extent of spatiotemporal associations among data sources to enhance data cleaning in sensor networks, a sensor stream reduction application, and also considers the use of Kalman filters for attack detection in a water system sensor network that consists of water level sensors and velocity sensors.

New Trends in Structural Health Monitoring
New Trends in Structural Health Monitoring

Author: Wieslaw Ostachowicz

Publisher: Springer Science & Business Media

Published: 2013-01-18

Total Pages: 433

ISBN-13: 3709113903

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A motivation for structural health monitoring. Structural health monitoring of aircraft structures. Vibration-based damage diagnosis and monitoring of external loads.Statistical time series methods for vibration based structural health monitoring. Fiber optic sensors. Damage localisation using elastic waves propagation methods experimental techniques. Application for wind turbine blades. Experts actively working in structural health monitoring and control techniques present the current research, areas of application and tendencies for the future of this technology, including various design issues involved. Examples using some of the latest hardware and software tools, experimental data from small scale laboratory demonstrators and measurements made on real structures illustrate the book. It will be a reference for professionals and students in the areas of engineering, applied natural sciences and engineering management.

Smart Sensors for Structural Health Monitoring
Smart Sensors for Structural Health Monitoring

Author: Simon Laflamme

Publisher: MDPI

Published: 2019-11-13

Total Pages: 342

ISBN-13: 3039217585

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Smart sensors are technologies designed to facilitate the monitoring operations. For instance, power consumption can be minimized through on-board processing and smart interrogation algorithms, and state detection enhanced through collaboration between sensor nodes. Applied to structural health monitoring, smart sensors are key enablers of sparse and dense sensor networks capable of monitoring full-scale structures and components. They are also critical in empowering operators with decision making capabilities. The objective of this Special Issue is to generate discussions on the latest advances in research on smart sensing technologies for structural health monitoring applications, with a focus on decision-enabling systems. This Special Issue covers a wide range of related topics such as innovative sensors and sensing technologies for crack, displacement, and sudden event monitoring, sensor optimization, and novel sensor data processing algorithms for damage and defect detection, operational modal analysis, and system identification of a wide variety of structures (bridges, transmission line towers, high-speed trains, masonry light houses, etc.).