New Trends in Vibration Based Structural Health Monitoring
1st Edition
Published on 28. January 2012
VII, 302 pages
978-3-7091-0399-9 (ISBN)
Description
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.
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Arnaud Deraemaeker | Keith Worden
New Trends in Vibration Based Structural Health Monitoring
Book
11/2014
Springer
€160.49
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Arnaud Deraemaeker | Keith Worden
New Trends in Vibration Based Structural Health Monitoring
Book
11/2010
Springer
€160.49
Shipment within 10-15 days
Content
- Intro
- Title Page
- Copyright Page
- PREFACE
- Table of Contents
- An Introduction to Structural Health Monitoring
- 1 Introduction
- 1.1 Montivation for SHM Technology Development
- 1.2 Motivation for this Book
- 2 Brief Historical Overview
- 3 The Statistical Pattern Recognition Paradigm
- 3.1 Operational Evaluation
- 3.2 Data Acquisition, Normalisation and Cleansing
- 3.3 Feature Extraction and Information Condensation
- 3.4 Statistical Model Development
- 4 Challenges for SHM
- 5 Concluding Remarks
- Bibliography
- Vibration Based Structural Health Monitoring Using Large Sensor Arrays: Overview of Instrumentation and Feature Extraction Based on Modal Filters
- 1 Sensors and Instrumentation for Vibration Based SHM
- 1.1 Most Common Transducer for SHM Applications
- 1.2 Acpuisition Units
- 1.3 Examples of Instrumented Bridges
- 1.4 Summary
- 2 Vibration-Based SHM Using Modal Filters
- 2.1 Introduction
- 2.2 Data Reduction Using Spatial and Modal Filters
- 2.3 Effect of Damage and Environment on Modal Filters
- 2.4 Feature Extraction Based on Modal Filter Outputs
- Bibliography
- Subspace identification for operational modal analysis
- 1 Introduction
- 2 State-space models of vibrating structures
- 2.1 Introduction
- 2.2 Linear dynamic finite element model
- 2.3 Continuous-time state-space model
- 2.4 Discrete-time state-space model
- 2.5 Modeling loads and sensor noise
- 2.6 A combined deterministic-stochastic state-space model
- 3 Subspace indentification: printciples and strategies
- 3.1 Introduction
- 3.2 System realisation
- 3.3 Subspace indentification
- 4 Subspace indentification: algorithms
- 4.1 Introduction
- 4.2 Covariance-driven stochastic subspace indentification
- 4.3 Data-driven stochastic subspace indentification
- 4.4 Data-driven combined deterministic-stochastic subspace indentification
- 5 Estimation of the modal parameters
- 5.1 Introduction
- 5.2 Estimation of the modal parameters
- 5.3 Distribution of the estimates
- 6 Applications
- 6.1 Introduction
- 6.2 Z24 bridge
- 6.3 Steel transmitter mast
- 7 Conclusions
- Bibliography
- Vibration-Based Structural Health Monitoring Under Variable Environmental or Operational Conditions
- 1 Introduction
- 2 Functions of a Structural Health Monitoring System
- 2.1 SHM Functions
- 2.2 Example
- 2.3 Summary
- 3 Sensor Validation
- 3.1 Minimum Mean Square Error (MMSE) Estimation
- 3.2 Experimental Results
- 3.3 Summary
- 4 Damage Detection Using Control Charts
- 4.1 Control Charts
- 4.2 Numerical Example
- 4.3 Summary
- 5 SHM Under Changing Environmental or Operational Conditions: Linear Models
- 5.1 Factor Analysis
- 5.2 Numerical Analysis
- 5.3 Wooden Bridge
- 5.4 Summary
- 6 SHM Under Changing Environmental or Operational Conditions: Nonlinear Models
- 6.1 Mixture of Factor Analysers
- 6.2 Numerical Analysis
- 6.3 The Z24 Bridge
- 6.4 Summary
- 7 Mechanical Engineering Application: A Hydraulic Crane
- 7.1 Features
- 7.2 Monitoring Experiments and Results
- 7.3 Summary
- 8 Conclusion
- Bibliography
- Structural Health Monitoring using Pattern Recognition
- 1 Introduction
- 2 Intelligent Fault Detection
- 2.1 Terminology
- 2.2 Intelligence
- 2.3 Data Processing and Fusion for Damage Identification
- 3 Novelty Detection
- 3.1 Gaussian-Distributed Normal Condition - Outlier Analysis
- 4 Neural Networks
- 4.1 Biological Neural Networks
- 4.2 The McCulloch-Pitts Neuron
- 4.3 Perceptrons
- 4.4 Multi-Layer Perceptrons
- 5 Novelty Detection Again
- 5.1 Non-Gaussian Normal Condition - Networks
- 6 Statistical Pattern Recognition
- 6.1 Statistical Pattern Recognition
- 6.2 Connection to Neural Networks
- 7 Experimental Illustrations
- 7.1 Level One - Damage Detection
- 7.2 Level Two - Damage Location
- 8 Discussion and Conclusions
- Bibliography
- 9 A Little Probability Theory
- Elastic Waves for Damage Detection in Structures
- 1 Introduction to SHM Methods Based on the Phenomenon of Elastic Wave Propagation
- 2 Modeling of Structural Stiffness Loss Due to Damage
- 2.1 discrete models
- 3 Lamb Waves
- 4 Modelling of Elastic Waves
- 4.1 The FFT-Based Spectral Finite Element Method - Cracked Rod
- 4.2 The Time Domain Spectral Element Method - Cracked Rod
- 4.3 Flexibility at the crack location
- 4.4 Comparative example
- 4.5 Influen of crack on wave propagation
- 5 Damage Indentification in 1D Structures
- 6 Experimental Applications of Lamb Waves
- 6.1 Test stand profile
- 6.2 Theoretical dispersion curves
- 6.3 Estimation and verification of wave group velocities
- 6.4 Damage detection
- 6.5 Crack detection
- 6.6 Conclusions
- Bibliography
