Structural Health Monitoring Using Genetic Fuzzy Systems
Structural health monitoring (SHM) has emerged as a prominent research area in recent years owing to increasing concerns about structural safety, and the need to monitor and extend the lives of existing structures. Structural Health Monitoring Using Genet
- PDF / 2,233,393 Bytes
- 135 Pages / 439.37 x 666.142 pts Page_size
- 56 Downloads / 200 Views
Prashant M. Pawar Ranjan Ganguli
Structural Health Monitoring Using Genetic Fuzzy Systems
Prashant M. Pawar College of Engineering Shri Vithal Education and Research Institute Pandharpur India [email protected]
Ranjan Ganguli Department of Aerospace Engineering Indian Institute of Science Bangalore India [email protected]
Additional material to this book can be downloaded from http://extras.springer.com. ISBN 978-0-85729-906-2 e-ISBN 978-0-85729-907-9 DOI 10.1007/978-0-85729-907-9 Springer London Dordrecht Heidelberg New York British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Control Number: 2011933278 © Springer-Verlag London Limited 2011 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licenses issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. The use of registered names, trademarks, etc., in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Cover design: VTeX UAB, Lithuania Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
Structural health monitoring (SHM) has emerged as an important research area in recent years because of its strong links with structural safety and the need to monitor and extend the lives of existing structures. SHM is an interdisciplinary field, combining elements of mechanics with those of information science and sensors and actuators. The practical importance of SHM is clear from the continuing failures which affect engineering structures such as bridges, aircraft, helicopters, and nuclear reactors. In many cases, a health monitoring system installed on the structure can detect and isolate the damage before it becomes catastrophic, thereby reducing the likelihood of failures. SHM systems can therefore reduce costs and save lives. A key problem in SHM involves performing damage detection and isolation from a set of measured data. Typically, the measured data is contaminated with noise, and the number of measurements is limited. In model-based SHM, a mathematical model is used to develop simulated measured data for the damaged structure. Then, the simulated data is used to develop a pattern recognition approach which maps the damage location and size to the simulate
Data Loading...
