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2010 | Buch

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New Trends in Vibration Based Structural Health Monitoring

herausgegeben von: Arnaud Deraemaeker, Keith Worden

Verlag: Springer Vienna

Buchreihe : CISM International Centre for Mechanical Sciences

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

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.

Inhaltsverzeichnis

Frontmatter

An Introduction to Structural Health Monitoring

Abstract

This introduction begins with a brief history of SHM technology development. Recent research has begun to recognise that a productive approach to the Structural Health Monitoring (SHM) problem is to regard it as one of statistical pattern recognition (SPR); a paradigm addressing the problem in such a way is described in detail herein as it forms the basis for the organisation of this book. In the process of providing the historical overview and summarising the SPR paradigm, the subsequent chapters in this book are cited in an effort to show how they fit into this overview of SHM. In the conclusions are stated a number of technical challenges that the authors believe must be addressed if SHM is to gain wider acceptance.

Charles R. Farrar, Keith Worden

Vibration Based Structural Health Monitoring Using Large Sensor Arrays: Overview of Instrumentation and Feature Extraction Based on Modal Filters

Abstract

Vibration based Structural Health Monitoring (SHM) techniques are based on the measurement of vibration signals on structures. The first part of this chapter is dedicated to an overview of the existing sensors and acquisition units which are available for such measurements, with an emphasis on recent advances in this area. With these recent advances in sensors and instrumentation, structures can be equipped with very large sensor arrays which monitor the vibration in real time. The difficulty is to be able to extract meaningful information from the huge amount of data generated by these large arrays. The second part of the chapter presents a data reduction technique based on modal filters. It is shown how features can be extracted from the output of these filters and subsequently used for damage detection.

Arnaud Deraemaeker

Subspace identification for operational modal analysis

Abstract

This chapter deals with the estimation of modal parameters from measured vibration data using subspace techniques. An in-depth review of subspace identification for operational modal analysis is provided. In addition, two recent developments are emphasised: the estimation of the probability density function of the modal parameters, and the use of an exogenous force in addition to the unmeasured operational excitation.

Edwin Reynders, Guido De Roeck

Vibration-Based Structural Health Monitoring Under Variable Environmental or Operational Conditions

Abstract

The main postulate in vibration-based structural health monitoring (SHM) is that structural damage can be detected from changes in the damage-sensitive features extracted from vibration measurements. In order to detect damage with a high sensitivity and reliability, several functions are needed. Control charts are applied to detect statistically significant changes in the features, sensor faults are identified using the minimum mean square error (MMSE) estimation, and the undesired effects of environmental or operational variations are removed using the linear factor analysis or the nonlinear mixture of linear factor analysers model. Different applications and data sets are analysed, including a wooden bridge and a vehicle crane.

Jyrki Kullaa

Structural Health Monitoring using Pattern Recognition

Abstract

There are two main approaches to the diagnostic phase of Structural Health Monitoring (SHM): the first, is based on the solution of inverse problems, and the second, is based on pattern recognition or machine learning. The first approach usually depends on the construction of a model of the structure based on physical principles, while the second relies on building a model based on measured data. The complexity of many modern structures and their environments sometimes makes the second option an attractive proposition. While many engineers are familiar with the process of building physics-based models e.g. finite element models, familiarity with the principles of pattern recognition is less common. The objective of this chapter is to provide an introduction to the concepts of data-based modelling and pattern recognition in the context of the SHM problem.

Keith Worden

Elastic Waves for Damage Detection in Structures

Abstract

The main issues regarding damage detection in elements of structures are discussed in the particular case that the detection is conducted by the use of methods based on the phenomenon of elastic wave propagation. The emphasis is placed on modelling the phenomenon of elastic wave propagation in composite elements of structures, along with issues of wave interactions with damage and problems of damage location.

Wieslaw Ostachowicz, Pawel Kudela

Titel: New Trends in Vibration Based Structural Health Monitoring
herausgegeben von: Arnaud Deraemaeker
Keith Worden
Verlag: Springer Vienna
Electronic ISBN: 978-3-7091-0399-9
Print ISBN: 978-3-7091-0398-2
DOI: https://doi.org/10.1007/978-3-7091-0399-9

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