"This book seeks to advance cutting-edge research in the field, with a special focus on cross-disciplinary work involving recent advances in IT, enabling structural-health experts to wield groundbreaking new models of artificial intelligence as a diagnostic tool capable of identifying future problems before they even appear"--Provided by publisher.

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 infrastructure systems are generally the most expensive assets in any country, and these systems are deteriorating at an alarming rate. In addition, these systems have a long service life in comparison to most other commercial products. As well, the introduction of intelligent materials and innovative design approaches in these systems is painfully slow due to heavy relianceon traditional construction and maintenance practices, and the conservative nature of design codes. Feedback on the "state of the health" of constructed systems is practically nonexistent. In the quest for lighter, stronger and corrosion-resistant structures, the replacement of ferrous materials by high-strength fibrous ones is being actively pursued in several countries around the world, both with respect to the design of new structures as well as for the rehabilitation and strengthening of existing ones. In North America, active research in the design of new highway bridges is focused on a number of specialty areas, including the replacement of steel reinforcing bars in concrete deck slabs by randomly distributed low-modulus fibers, and the replacement of steel prestressing cables for concrete components by tendons comprising super-strong fibers. Research is also being conducted on using FRPs to repair and strengthen existing structures.

This book is devoted to a special class of engineering problems called Bayesian inverse problems. These problems comprise not only the probabilistic Bayesian formulation of engineering problems, but also the associated stochastic simulation methods needed to solve them. Through this book, the reader will learn how this class of methods can be useful to rigorously address a range of engineering problems where empirical data and fundamental knowledge come into play. The book is written for a non-expert audience and it is contributed to by many of the most renowned academic experts in this field.

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.

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.

The rail-based transit system is a popular public transportation option, not just with members of the public but also with policy makers looking to install a form of convenient and rapid travel. Even for moving bulk freight long distances, a rail-based system is the most sustainable transportation system currently available. The Handbook of Research on Emerging Innovations in Rail Transportation Engineering presents the latest research on next-generation public transportation infrastructures. Emphasizing a diverse set of topics related to rail-based transportation such as funding issues, policy design, traffic planning and forecasting, and engineering solutions, this comprehensive publication is an essential resource for transportation planners, engineers, policymakers, and graduate-level engineering students interested in uncovering research-based solutions, recommendations, and examples of modern rail transportation systems.