Structural Health Monitoring

Inbunden, Engelska, 2006

Av Daniel Balageas, Daniel Balageas, Claus-Peter Fritzen, Alfredo Güemes

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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.

Produktinformation

Utgivningsdatum2006-01-22
Mått160 x 236 x 33 mm
Vikt1 021 g
FormatInbunden
SpråkEngelska
Antal sidor496
FörlagISTE Ltd and John Wiley & Sons Inc
ISBN9781905209019

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Foreword 11Chapter 1. Introduction to Structural Health Monitoring 13Daniel BALAGEAS1.1. Definition of Structural Health Monitoring 131.2. Motivation for Structural Health Monitoring 151.3. Structural Health Monitoring as a way of making materials and structures smart 181.4. SHM and biomimetics 211.5. Process and pre-usage monitoring as a part of SHM 241.6. SHM as a part of system management 261.7. Passive and active SHM 271.8. NDE, SHM and NDECS 281.9. Variety and multidisciplinarity: the most remarkable characters of SHM 321.10. Birth of the Structural Health Monitoring Community 361.11. Conclusion 381.12. References 39Chapter 2. Vibration-Based Techniques for Structural Health Monitoring 45Claus-Peter FRITZEN2.1. Introduction 452.2. Basic vibration concepts for SHM 492.2.1. Local and global methods 522.2.2. Damage diagnosis as an inverse problem 542.2.3. Model-based damage assessment 572.3. Mathematical description of structural systems with damage 622.3.1. General dynamic behavior 622.3.2. State-space description of mechanical systems 652.3.3. Modeling of damaged structural elements 732.4. Linking experimental and analytical data 772.4.1. Modal Assurance Criterion (MAC) for mode pairing 772.4.2. Modal Scaling Factor (MSF) 782.4.3. Co-ordinate Modal Assurance Criterion (COMAC) 792.4.4. Damping 792.4.5. Expansion and reduction 802.4.6. Updating of the initial model 842.5. Damage localization and quantification 882.5.1. Change of the flexibility matrix 882.5.2. Change of the stiffness matrix 902.5.3. Strain-energy-based indicator methods and curvature modes 912.5.4. MECE error localization technique 952.5.5. Static displacement method 962.5.6. Inverse eigensensitivity method 972.5.7. Modal force residual method 1002.5.8. Kinetic and strain energy-based sensitivity methods 1042.5.9. Forced vibrations and frequency response functions 1082.6. Solution of the equation system 1182.6.1. Regularization 1192.6.2. Parameter subset selection 1202.6.3. Other solution methods 1252.6.4. Variances of the parameters 1262.7. Neural network approach to SHM 1272.7.1. The basic idea of neural networks 1282.7.2. Neural networks in damage detection, localization and quantification 1292.7.3. Multi-layer Perceptron (MLP) 1312.8. A simulation example 1322.8.1. Description of the structure 1322.8.2. Application of damage indicator methods 1372.8.3. Application of the modal force residual method and inverse eigensensitivity method 1422.8.4. Application of the kinetic and modal strain energy methods 1492.8.5. Application of the Multi-Layer Perceptron neural network 1522.9. Time-domain damage detection methods for linear systems 1532.9.1. Parity equation method 1542.9.2. Kalman filters 1632.9.3. AR and ARX models 1682.10. Damage identification in non-linear systems 1682.10.1. Extended Kalman filter 1682.10.2. Localization of damage using filter banks 1712.10.3. A simulation study on a beam with opening and closing crack 1722.11. Applications 1772.11.1. I-40 bridge 1772.11.2. Steelquake structure 1852.11.3. Application of the Z24 bridge 1922.11.4. Detection of delamination in a CFRP plate with stiffeners 1982.12. Conclusion 2052.13. Acknowledgements 2072.14. References 208Chapter 3. Fiber-Optic Sensors 225Alfredo GÜEMES and Jose Manuel MENENDEZ3.1. Introduction 2253.2. Classification of fiber-optic sensors 2293.2.1. Intensity-based sensors 2293.2.2. Phase-modulated optical fiber sensors, or interferometers 2323.2.3. Wavelength based sensors, or Fiber Bragg Gratings (FBG) 2353.3. The fiber Bragg grating as a strain and temperature sensor 2373.3.1. Response of the FBG to uniaxial uniform strain fields 2373.3.2. Sensitivity of the FBG to temperature 2393.3.3. Response of the FBG to a non-uniform uniaxial strain field 2403.3.4. Response of the FBG to transverse stresses 2483.3.5. Photoelasticity in a plane stress state 2513.4. Structures with embedded fiber Bragg gratings 2623.4.1. Orientation of the optical fiber optic with respect to the reinforcement fibers 2633.4.2. Ingress/egress from the laminate 2653.5. Fiber Bragg gratings as damage sensors for composites 2653.5.1. Measurement of strain and stress variations 2663.5.2. Measurement of spectral perturbations associated with internal stress release resulting from damage spread 2703.6. Examples of applications in aeronautics and civil engineering 2743.6.1. Stiffened panels with embedded fiber Bragg gratings 2753.6.2. Concrete beam repair 2813.7. Conclusions 2833.8. References 284Chapter 4. Structural Health Monitoring with Piezoelectric Sensors 287Philippe GUY and Thomas MONNIER4.1. Background and context 2874.2. The use of embedded sensors as acoustic emission (AE) detectors 2904.2.1. Experimental results and conventional analysis of acoustic emission signals 2934.2.2. Algorithms for damage localization 2964.2.3. Algorithms for damage characterization 3004.2.4. Available industrial AE systems 3044.2.5. New concepts in acoustic emission 3054.2.6. Conclusion 3084.3. State-the-art and main trends in piezoelectric transducer-based acousto-ultrasonic SHM research 3084.3.1. Lamb wave structure interrogation 3094.3.2. Sensor technology 3134.3.3. Tested structures (mainly metallic or composite parts) 3254.3.4. Acousto-ultrasonic signal and data reduction methods 3254.3.5. The full implementation of SHM of localized damage with guided waves in composite materials 3344.3.6. Available industrial acousto-ultrasonic systems with piezoelectric sensors 3474.4. Electromechanical impedance 3524.4.1.E/M impedance for defect detection in metallic and composite parts 3524.4.2. The piezoelectric implant method applied to the evaluation and monitoring of viscoelastic properties 3534.4.3. Conclusion 3644.5. Summary and guidelines for future work 3654.6. References 365Chapter 5. SHM Using Electrical Resistance 379Michelle SALVIA and Jean-Christophe ABRY5.1. Introduction 3795.2. Composite damage 3805.3. Electrical resistance of unloaded composite 3815.3.1. Percolation concept 3815.3.2. Anisotropic conduction properties in continuous fiber reinforced polymer 3825.3.3. Influence of temperature 3865.4. Composite strain and damage monitoring by electrical resistance 3885.4.1. 0° unidrectional laminates 3885.4.2. Multidirectional laminates 3965.4.3. Randomly distributed fiber reinforced polymers 4015.5. Damage localization 4015.6. Conclusion 4055.7. References 405Chapter 6. Low Frequency Electromagnetic Techniques 411Michel LEMISTRE6.1. Introduction 4116.2. Theoretical considerations on electromagnetic theory 4126.2.1. Maxwell’s equations 4126.2.2. Dipole radiation 4136.2.3. Surface impedance 4166.2.4. Diffraction by a circular aperture 4216.2.5. Eddy currents 4236.2.6. Polarization of dielectrics 4236.3. Applications to the NDE/NDT domain 4266.3.1. Dielectric materials 4266.3.2. Conductive materials 4286.3.3. Hybrid method 4326.4. Signal processing 4366.4.1. Time-frequency transforms 4366.4.2. The continuous wavelet transform 4376.4.3. The discrete wavelet transform 4396.4.4. Multiresolution 4416.4.5. Denoising 4436.5. Application to the SHM domain 4476.5.1. General principles 4476.5.2. Magnetic method 4486.5.3. Electric method 4506.5.4. Hybrid method 4506.6. References 460Chapter 7. Capacitive Methods for Structural Health Monitoring in Civil Engineering 463Xavier DÉROBERT and Jean IAQUINTA7.1. Introduction 4637.2. The principle 4647.3. Capacitance probe for cover concrete 4667.3.1. Layout 4667.3.2. Sensitivity 4677.3.3. Example of measurements on the Empalot Bridge (Toulouse, France) 4697.4. Application for external post-tensioned cables 4717.4.1. Influence of the location of the cable 4737.4.2. Effect of air and water layers 4747.4.3. Small inclusions 4767.4.4. Example of an actual measurement 4777.5. Future work 4797.6. Monitoring historical buildings 4807.6.1. Capacitance probe for moisture monitoring 4817.6.2. Environmental conditions 4827.6.3. Study on a stone wall test site 4837.6.4. Water content monitoring of part of the masonry of Notre-Dame La Grande church (Poitiers, France) 4857.7. Conclusion 4887.8. Acknowledgements 4887.9. References 489Short Biographies of the Contributors 491Index 493