Structural Health Monitoring With Application To Offshore Structures

Structural Health Monitoring (SHM) deals with assessment, evaluation and technical diagnosis of different structural systems of strategic importance. Extensive knowledge of SHM shall lead to a clear understanding of risk and reliability assessment of structures, which is currently mandatory for structures of strategic importance like bridges, offshore structures, etc.This comprehensive compendium features explanations and salient illustrations of SHM with applications to civil engineering structures, in general and offshore structures, in particular. The book is unique with respect to its contents, experimental case studies in lab scale and text presentation style. A detailed subject matter of this nature is currently scarce in the literature market.The must-have volume is a useful reference text for senior undergraduate and postgraduate students, professionals, academics and researchers in civil engineering, ocean engineering, mechanical engineering, and structural engineering.

A critical review of key developments and latest advances in Structural Health Monitoring technologies applied to civil engineering structures, covering all aspects required for practical application Structural Health Monitoring (SHM) provides the facilities for in-service monitoring of structural performance and damage assessment, and is a key element of condition based maintenance and damage prognosis. This comprehensive book brings readers up to date on the most important changes and advancements in the structural health monitoring technologies applied to civil engineering structures. It covers all aspects required for such monitoring in the field, including sensors and networks, data acquisition and processing, damage detection techniques and damage prognostics techniques. The book also includes a number of case studies showing how the techniques can be applied in the development of sustainable and resilient civil infrastructure systems. Structural Health Monitoring of Large Civil Engineering Structures offers in-depth chapter coverage of: Sensors and Sensing Technology for Structural Monitoring; Data Acquisition, Transmission, and Management; Structural Damage Identification Techniques; Modal Analysis of Civil Engineering Structures; Finite Element Model Updating; Vibration Based Damage Identification Methods; Model Based Damage Assessment Methods; Monitoring Based Reliability Analysis and Damage Prognosis; and Applications of SHM Strategies to Large Civil Structures. Presents state-of-the-art SHM technologies allowing asset managers to evaluate structural performance and make rational decisions Covers all aspects required for the practical application of SHM Includes case studies that show how the techniques can be applied in practice Structural Health Monitoring of Large Civil Engineering Structures is an ideal book for practicing civil engineers, academics and postgraduate students studying civil and structural engineering.

HEALTH MONITORING OF OFFSHORE STRUCTURES This Book explores the structural health monitoring of offshore structures subjected to harsh environments using major search techniques of artificial intelligence (AI) "neural networks, and fuzzy logic". Evaluation of the marine environment as represented by waves, wind, and currents is explained. For each marine environment, the natural frequency and deck drifts, which may approximately represent a defectedcriterion is calculated. Modeling of offshore structures with finite elements is illustrated for offshore steel structures. The effective application of modern and standard computer software NASTRAN package to model the offshore structures is presented. The motivation in this study is to investigate the possibility of building a common framework that can accommodate both numerical data and linguistic rules through the integration of a neural network and a fuzzy system, so that experimental data and human experience can be combined in developing intelligent system.

Structural Health Monitoring with Piezoelectric Wafer Active Sensors, Second Edition provides an authoritative theoretical and experimental guide to this fast-paced, interdisciplinary area with exciting applications across a range of industries. The book begins with a detailed yet digestible consolidation of the fundamental theory relating to structural health monitoring (SHM). Coverage of fracture and failure basics, relevant piezoelectric material properties, vibration modes in different structures, and different wave types provide all the background needed to understand SHM and apply it to real-world structural challenges. Moving from theory to experimental practice, the book then provides the most comprehensive coverage available on using piezoelectric wafer active sensors (PWAS) to detect and quantify damage in structures. Updates to this edition include circular and straight-crested Lamb waves from first principle, and the interaction between PWAS and Lamb waves in 1-D and 2-D geometries. Effective shear stress is described, and tuning expressions between PWAS and Lamb waves has been extended to cover axisymmetric geometries with a complete Hankel-transform-based derivation. New chapters have been added including hands-on SHM case studies of PWAS stress, strain, vibration, and wave sensing applications, along with new sections covering essential aspects of vibration and wave propagation in axisymmetric geometries. Comprehensive coverage of underlying theory such as piezoelectricity, vibration, and wave propagation alongside experimental techniques Includes step-by-step guidance on the use of piezoelectric wafer active sensors (PWAS) to detect and quantify damage in structures, including clear information on how to interpret sensor signal patterns Updates to this edition include a new chapter on composites and new sections on advances in vibration and wave theory, bringing this established reference in line with the cutting edge in this emerging area

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.

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

Presents the research and applications on sensing technologies to monitor and control the structure and health of buildings, bridges, installations, and other constructed facilities.

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.

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 costs Analyzes current SHM technologies and sensing systems, highlighting the innovation in each area Encompasses chapters on smart materials such as electroactive polymers and optical fibers