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Important new information on sensors, monitoring, prognosis, networking, and planning for safety and maintenance.
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.
These proceedings of the Third European Workshop on Structural Health Monitoring held at the Conference Centre in Granada, Spain, in July of 2006 includes four keynote presentations and 170 technical papers written by an international group of contributors. Papers discuss technology and activities related to damage detection and evaluation in engin
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.
This book is a collection of articles covering the six lecture courses given at the CISM School on this topic in 2008. It features contributions by established international experts and offers a coherent and comprehensive overview of the state-of-the art research in the field, thus addressing both postgraduate students and researchers in aerospace, mechanical and civil engineering.
This open access book presents established methods of structural health monitoring (SHM) and discusses their technological merit in the current aerospace environment. While the aerospace industry aims for weight reduction to improve fuel efficiency, reduce environmental impact, and to decrease maintenance time and operating costs, aircraft structures are often designed and built heavier than required in order to accommodate unpredictable failure. A way to overcome this approach is the use of SHM systems to detect the presence of defects. This book covers all major contemporary aerospace-relevant SHM methods, from the basics of each method to the various defect types that SHM is required to detect to discussion of signal processing developments alongside considerations of aerospace safety requirements. It will be of interest to professionals in industry and academic researchers alike, as well as engineering students. This article/publication is based upon work from COST Action CA18203 (ODIN - http://odin-cost.com/), supported by COST (European Cooperation in Science and Technology). COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation.
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
The range of fibre-reinforced polymer (FRP) applications in new construction, and in the retrofitting of existing civil engineering infrastructure, is continuing to grow worldwide. Furthermore, this progress is being matched by advancing research into all aspects of analysis and design. The Second International Conference on FRP Composites in
The book focuses especially on the application of SHM technology to thin walled structural systems made from carbon fiber reinforced plastics. Here, guided elastic waves (Lamb-waves) show an excellent sensitivity to structural damages so that they are in the center of this book. It is divided into 4 sections dealing with analytical, numerical and experimental fundamentals, and subsequently with Lamb-wave propagation in fiber reinforced composites, SHM-systems and signal processing. The book is designed for engineering students as well as for researchers in the field of structural health monitoring and for users of this technology.
The first complete introduction to health monitoring, encapsulating both technical information and practical case studies spanning the breadth of the subject. Written by a highly-respected figure in structural health monitoring, this book provides readers with the technical skills and practical understanding required to solve new problems encountered in the emerging field of health monitoring. The book presents a suite of methods and applications in loads identification (usage monitoring), in-situ damage identification (diagnostics), and damage and performance prediction (prognostics). Concepts in modelling, measurements, and data analysis are applied through real-world case studies to identify loading, assess damage, and predict the performance of structural components, as well as examine engine components, automotive accessories, aircraft parts, spacecraft components, civil structures and defence system components. In particular the book: provides the reader with a fundamental and practical understanding of the material; discusses models demonstrating the physical basis for health monitoring techniques; gives a detailed review of the best practices in dynamic measurements including sensing; presents numerous data analysis techniques using model- and signal-based methods; discusses case studies involving real-world applications of health monitoring; offers end-of-chapter problems to enhance the study of the topic for students and instructors; and includes an accompanying website with MATLAB programs providing hands-on training to readers for writing health monitoring model simulation and data analysis algorithms. Health Monitoring of Structural Materials and Components is an excellent introductory text for newcomers to the subject as well as an excellent study tool for students and lecturers. Practitioners and researchers, those with a greater understanding and application of the technical skills involved, will also find this essential reading as a reference text to address current and future challenges in this field. The wide variety of case studies will appeal to a broad spectrum of engineers in the aerospace, civil, mechanical, machinery and defence communities.