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Data-Centric Structural Health Monitoring

Author: Mohammad Noori

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2023-09-04

Total Pages: 359

ISBN-13: 311079151X

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

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.

Data-Centric Structural Health Monitoring

Author: Mohammad Noori

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2023-09-04

Total Pages: 274

ISBN-13: 3110791420

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Data Driven Methods for Civil Structural Health Monitoring and Resilience

Author: Mohammad Noori

Publisher: CRC Press

Published: 2023-10

Total Pages: 0

ISBN-13: 9781032308371

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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

Author: Daniel Balageas

Publisher: John Wiley & Sons

Published: 2010-01-05

Total Pages: 496

ISBN-13: 0470394404

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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.

Data Driven Methods for Civil Structural Health Monitoring and Resilience

Author: Mohammad Noori

Publisher:

Published: 2024

Total Pages: 0

ISBN-13: 9781003306924

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"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 able to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis"--

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.

Data Driven Methods for Civil Structural Health Monitoring and Resilience

Author: Mohammad Noori

Publisher: CRC Press

Published: 2023-10-26

Total Pages: 459

ISBN-13: 1000965589

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Structural Health Monitoring For Advanced Composite Structures

Author: Aliabadi M H Ferri

Publisher: World Scientific

Published: 2017-12-18

Total Pages: 288

ISBN-13: 1786343940

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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

Structural Health Monitoring

Author: Charles R. Farrar

Publisher: John Wiley & Sons

Published: 2012-11-19

Total Pages: 735

ISBN-13: 1118443217

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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.