Structural Health Monitoring

Foreword 11

Chapter 1. Introduction to Structural Health Monitoring 13
Daniel BALAGEAS

1.1. Definition of Structural Health Monitoring 13

1.2. Motivation for Structural Health Monitoring 15

1.3. Structural Health Monitoring as a way of making materials and structures smart 18

1.4. SHM and biomimetics 21

1.5. Process and pre-usage monitoring as a part of SHM 24

1.6. SHM as a part of system management 26

1.7. Passive and active SHM 27

1.8. NDE, SHM and NDECS 28

1.9. Variety and multidisciplinarity: the most remarkable characters of SHM 32

1.10. Birth of the Structural Health Monitoring Community 36

1.11. Conclusion 38

1.12. References 39

Chapter 2. Vibration-Based Techniques for Structural Health Monitoring 45
Claus-Peter FRITZEN

2.1. Introduction 45

2.2. Basic vibration concepts for SHM 49

2.2.1. Local and global methods 52

2.2.2. Damage diagnosis as an inverse problem 54

2.2.3. Model-based damage assessment 57

2.3. Mathematical description of structural systems with damage 62

2.3.1. General dynamic behavior 62

2.3.2. State-space description of mechanical systems 65

2.3.3. Modeling of damaged structural elements 73

2.4. Linking experimental and analytical data 77

2.4.1. Modal Assurance Criterion (MAC) for mode pairing 77

2.4.2. Modal Scaling Factor (MSF) 78

2.4.3. Co-ordinate Modal Assurance Criterion (COMAC) 79

2.4.4. Damping 79

2.4.5. Expansion and reduction 80

2.4.6. Updating of the initial model 84

2.5. Damage localization and quantification 88

2.5.1. Change of the flexibility matrix 88

2.5.2. Change of the stiffness matrix 90

2.5.3. Strain-energy-based indicator methods and curvature modes 91

2.5.4. MECE error localization technique 95

2.5.5. Static displacement method 96

2.5.6. Inverse eigensensitivity method 97

2.5.7. Modal force residual method 100

2.5.8. Kinetic and strain energy-based sensitivity methods 104

2.5.9. Forced vibrations and frequency response functions 108

2.6. Solution of the equation system 118

2.6.1. Regularization 119

2.6.2. Parameter subset selection 120

2.6.3. Other solution methods 125

2.6.4. Variances of the parameters 126

2.7. Neural network approach to SHM 127

2.7.1. The basic idea of neural networks 128

2.7.2. Neural networks in damage detection, localization and quantification 129

2.7.3. Multi-layer Perceptron (MLP) 131

2.8. A simulation example 132

2.8.1. Description of the structure 132

2.8.2. Application of damage indicator methods 137

2.8.3. Application of the modal force residual method and inverse eigensensitivity method 142

2.8.4. Application of the kinetic and modal strain energy methods 149

2.8.5. Application of the Multi-Layer Perceptron neural network 152

2.9. Time-domain damage detection methods for linear systems 153

2.9.1. Parity equation method 154

2.9.2. Kalman filters 163

2.9.3. AR and ARX models 168

2.10. Damage identification in non-linear systems 168

2.10.1. Extended Kalman filter 168

2.10.2. Localization of damage using filter banks 171

2.10.3. A simulation study on a beam with opening and closing crack 172

2.11. Applications 177

2.11.1. I-40 bridge 177

2.11.2. Steelquake structure 185

2.11.3. Application of the Z24 bridge 192

2.11.4. Detection of delamination in a CFRP plate with stiffeners 198

2.12. Conclusion 205

2.13. Acknowledgements 207

2.14. References 208

Chapter 3. Fiber-Optic Sensors 225
Alfredo GÜEMES and Jose Manuel MENENDEZ

3.1. Introduction 225

3.2. Classification of fiber-optic sensors 229

3.2.1. Intensity-based sensors 229

3.2.2. Phase-modulated optical fiber sensors, or interferometers 232

3.2.3. Wavelength based sensors, or Fiber Bragg Gratings (FBG) 235

3.3. The fiber Bragg grating as a strain and temperature sensor 237

3.3.1. Response of the FBG to uniaxial uniform strain fields 237

3.3.2. Sensitivity of the FBG to temperature 239

3.3.3. Response of the FBG to a non-uniform uniaxial strain field 240

3.3.4. Response of the FBG to transverse stresses 248

3.3.5. Photoelasticity in a plane stress state 251

3.4. Structures with embedded fiber Bragg gratings 262

3.4.1. Orientation of the optical fiber optic with respect to the reinforcement fibers 263

3.4.2. Ingress/egress from the laminate 265

3.5. Fiber Bragg gratings as damage sensors for composites 265

3.5.1. Measurement of strain and stress variations 266

3.5.2. Measurement of spectral perturbations associated with internal stress release resulting from damage spread 270

3.6. Examples of applications in aeronautics and civil engineering 274

3.6.1. Stiffened panels with embedded fiber Bragg gratings 275

3.6.2. Concrete beam repair 281

3.7. Conclusions 283

3.8. References 284

Chapter 4. Structural Health Monitoring with Piezoelectric Sensors 287
Philippe GUY and Thomas MONNIER

4.1. Background and context 287

4.2. The use of embedded sensors as acoustic emission (AE) detectors 290

4.2.1. Experimental results and conventional analysis of acoustic emission signals 293

4.2.2. Algorithms for damage localization 296

4.2.3. Algorithms for damage characterization 300

4.2.4. Available industrial AE systems 304

4.2.5. New concepts in acoustic emission 305

4.2.6. Conclusion 308

4.3. State-the-art and main trends in piezoelectric transducer-based acousto-ultrasonic SHM research 308

4.3.1. Lamb wave structure interrogation 309

4.3.2. Sensor technology 313

4.3.3. Tested structures (mainly metallic or composite parts) 325

4.3.4. Acousto-ultrasonic signal and data reduction methods 325

4.3.5. The full implementation of SHM of localized damage with guided waves in composite materials 334

4.3.6. Available industrial acousto-ultrasonic systems with piezoelectric sensors 347

4.4. Electromechanical impedance 352

4.4.1.E/M impedance for defect detection in metallic and composite parts 352

4.4.2. The piezoelectric implant method applied to the evaluation and monitoring of viscoelastic properties 353

4.4.3. Conclusion 364

4.5. Summary and guidelines for future work 365

4.6. References 365

Chapter 5. SHM Using Electrical Resistance 379
Michelle SALVIA and Jean-Christophe ABRY

5.1. Introduction 379

5.2. Composite damage 380

5.3. Electrical resistance of unloaded composite 381

5.3.1. Percolation concept 381

5.3.2. Anisotropic conduction properties in continuous fiber reinforced polymer 382

5.3.3. Influence of temperature 386

5.4. Composite strain and damage monitoring by electrical resistance 388

5.4.1. 0° unidrectional laminates 388

5.4.2. Multidirectional laminates 396

5.4.3. Randomly distributed fiber reinforced polymers 401

5.5. Damage localization 401

5.6. Conclusion 405

5.7. References 405

Chapter 6. Low Frequency Electromagnetic Techniques 411
Michel LEMISTRE

6.1. Introduction 411

6.2. Theoretical considerations on electromagnetic theory 412

6.2.1. Maxwell’s equations 412

6.2.2. Dipole radiation 413

6.2.3. Surface impedance 416

6.2.4. Diffraction by a circular aperture 421

6.2.5. Eddy currents 423

6.2.6. Polarization of dielectrics 423

6.3. Applications to the NDE/NDT domain 426

6.3.1. Dielectric materials 426

6.3.2. Conductive materials 428

6.3.3. Hybrid method 432

6.4. Signal processing 436

6.4.1. Time-frequency transforms 436

6.4.2. The continuous wavelet transform 437

6.4.3. The discrete wavelet transform 439

6.4.4. Multiresolution  441

6.4.5. Denoising 443

6.5. Application to the SHM domain 447

6.5.1. General principles 447

6.5.2. Magnetic method 448

6.5.3. Electric method 450

6.5.4. Hybrid method 450

6.6. References 460

Chapter 7. Capacitive Methods for Structural Health Monitoring in Civil Engineering 463
Xavier DÉROBERT and Jean IAQUINTA

7.1. Introduction 463

7.2. The principle 464

7.3. Capacitance probe for cover concrete 466

7.3.1. Layout 466

7.3.2. Sensitivity 467

7.3.3. Example of measurements on the Empalot Bridge (Toulouse, France) 469

7.4. Application for external post-tensioned cables 471

7.4.1. Influence of the location of the cable 473

7.4.2. Effect of air and water layers 474

7.4.3. Small inclusions 476

7.4.4. Example of an actual measurement 477

7.5. Future work 479

7.6. Monitoring historical buildings 480

7.6.1. Capacitance probe for moisture monitoring 481

7.6.2. Environmental conditions 482

7.6.3. Study on a stone wall test site 483

7.6.4. Water content monitoring of part of the masonry of Notre-Dame La Grande church (Poitiers, France) 485

7.7. Conclusion 488

7.8. Acknowledgements 488

7.9. References 489

Short Biographies of the Contributors 491

Index 493