Structural Health Monitoring

, by Balageas, Daniel; Fritzen, Claus-Peter; Gü; emes, Alfredo

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ISBN: 9781905209019 | 1905209010
Cover: Hardcover
Copyright: 2/6/2006

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While exploring the variety of sensing techniques used to achieve structural health monitoring, this book focuses on the sensors, signal- and data-reduction methods, and inverse techniques. Because the techniques are not based upon application type or linked to special classes of problems, the book explores the broader familiesvibration and modal analysis, optical fibre sensing, acousto-ultrasonics using piezoelectric transducers, and electric and electromagnetic techniques.

Foreword

(2)

Chapter 1. Introduction to Structural Health Monitoring

(32)

Daniel BALAGEAS

1.1. Definition of Structural Health Monitoring

(2)

1.2. Motivation for Structural Health Monitoring

(3)

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

(3)

1.4. SHM and biomimetics

(3)

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

(2)

1.6. SHM as a part of system management

(1)

1.7. Passive and active SHM

(1)

1.8. NDE, SHM and NDECS

(4)

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

(4)

1.10. Birth of the Structural Health Monitoring Community

(2)

1.11. Conclusion

(1)

1.12. References

(6)

Chapter 2. Vibration-Based Techniques for Structural Health Monitoring

(180)

Claus-Peter FRITZEN

2.1. Introduction

(4)

2.2. Basic vibration concepts for SHM

(13)

2.2.1. Local and global methods

(2)

2.2.2. Damage diagnosis as an inverse problem

(3)

2.2.3. Model-based damage assessment

(5)

2.3. Mathematical description of structural systems with damage

(15)

2.3.1. General dynamic behavior

(3)

2.3.2. State-space description of mechanical systems

(8)

2.3.3. Modeling of damaged structural elements

(4)

2.4. Linking experimental and analytical data

(11)

2.4.1. Modal Assurance Criterion (MAC) for mode pairing

(1)

2.4.2. Modal Scaling Factor (MSF)

(1)

2.4.3. Co-ordinate Modal Assurance Criterion (COMAC)

(1)

2.4.4. Damping

(1)

2.4.5. Expansion and reduction

(4)

2.4.6. Updating of the initial model

(4)

2.5. Damage localization and quantification

(30)

2.5.1. Change of the flexibility matrix

(2)

2.5.2. Change of the stiffness matrix

(1)

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

(4)

2.5.4. MECE error localization technique

(1)

2.5.5. Static displacement method

(1)

2.5.6. Inverse eigensensitivity method

(3)

2.5.7. Modal force residual method

100

(4)

2.5.8. Kinetic and strain energy-based sensitivity methods

104

(4)

2.5.9. Forced vibrations and frequency response functions

108

(10)

2.6. Solution of the equation system

118

(9)

2.6.1. Regularization

119

(1)

2.6.2. Parameter subset selection

120

(5)

2.6.3. Other solution methods

125

(1)

2.6.4. Variances of the parameters

126

(1)

2.7. Neural network approach to SHM

127

(5)

2.7.1. The basic idea of neural networks

128

(1)

2.7.2. Neural networks in damage detection, localization and quantification

129

(2)

2.7.3. Multi-layer Perceptron (MLP)

131

(1)

2.8. A simulation example

132

(21)

2.8.1. Description of the structure

132

(5)

2.8.2. Application of damage indicator methods

137

(5)

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

142

(7)

2.8.4. Application of the kinetic and modal strain energy methods

149

(3)

2.8.5. Application of the Multi-Layer Perceptron neural network

152

(1)

2.9. Time-domain damage detection methods for linear systems

153

(15)

2.9.1. Parity equation method

154

(9)

2.9.2. Kalman filters

163

(5)

2.9.3. AR and ARX models

168

(1)

2.10. Damage identification in non-linear systems

168

(9)

2.10.1. Extended Kalman filter

168

(3)

2.10.2. Localization of damage using filter banks

171

(1)

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

172

(5)

2.11. Applications

177

(28)

2.11.1. I-40 bridge

177

(8)

2.11.2. Steelquake structure

185

(7)

2.11.3. Application of the Z24 bridge

192

(6)

2.11.4. Detection of delamination in a CFRP plate with stiffeners

198

(7)

2.12. Conclusion

205

(2)

2.13. Acknowledgements

207

(1)

2.14. References

208

(17)

Chapter 3. Fiber-Optic Sensors

225

(62)

Alfredo GÜEMES and Jose Manuel MENENDEZ

3.1. Introduction

225

(4)

3.2. Classification of fiber-optic sensors

229

(8)

3.2.1. Intensity-based sensors

229

(3)

3.2.2. Phase-modulated optical fiber sensors, or interferometers

232

(3)

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

235

(2)

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

237

(25)

3.3.1. Response of the FBG to uniaxial uniform strain fields

237

(2)

3.3.2. Sensitivity of the FBG to temperature

239

(1)

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

240

(8)

3.3.4. Response of the FBG to transverse stresses

248

(3)

3.3.5. Photoelasticity in a plane stress state

251

(11)

3.4. Structures with embedded fiber Bragg gratings

262

(3)

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

263

(2)

3.4.2. Ingress/egress from the laminate

265

(1)

3.5. Fiber Bragg gratings as damage sensors for composites

265

(9)

3.5.1. Measurement of strain and stress variations

266

(4)

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

270

(4)

3.6. Examples of applications in aeronautics and civil engineering

274

(9)

3.6.1. Stiffened panels with embedded fiber Bragg gratings

275

(6)

3.6.2. Concrete beam repair

281

(2)

3.7. Conclusions

283

(1)

3.8. References

284

(3)

Chapter 4. Structural Health Monitoring with Piezoelectric Sensors

287

(92)

Philippe GUY and Thomas MONNIER

4.1. Background and context

287

(3)

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

290

(18)

4.2.1. Experimental results and conventional analysis of acoustic emission signals

293

(3)

4.2.2. Algorithms for damage localization

296

(4)

4.2.3. Algorithms for damage characterization

300

(4)

4.2.4. Available industrial AE systems

304

(1)

4.2.5. New concepts in acoustic emission

305

(3)

4.2.6. Conclusion

308

(1)

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

308

(44)

4.3.1. Lamb wave structure interrogation

309

(4)

4.3.2. Sensor technology

313

(12)

4.3.3. Tested structures (mainly metallic or composite parts)

325

(1)

4.3.4. Acousto-ultrasonic signal and data reduction methods

325

(9)

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

334

(13)

4.3.6. Available industrial acousto-ultrasonic systems with piezoelectric sensors

347

(5)

4.4. Electromechanical impedance

352

(13)

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

352

(1)

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

353

(11)

4.4.3. Conclusion

364

(1)

4.5. Summary and guidelines for future work

365

(1)

4.6. References

365

(14)

Chapter 5. SHM Using Electrical Resistance

379

(32)

Michelle SALVIA and Jean-Christophe ABRY

5.1. Introduction

379

(1)

5.2. Composite damage

380

(1)

5.3. Electrical resistance of unloaded composite

381

(7)

5.3.1. Percolation concept

381

(1)

5.3.2. Anisotropic conduction properties in continuous fiber reinforced polymer

382

(4)

5.3.3. Influence of temperature

386

(2)

5.4. Composite strain and damage monitoring by electrical resistance

388

(13)

5.4.1. 0° unidrectional laminates

388

(8)

5.4.2. Multidirectional laminates

396

(5)

5.4.3. Randomly distributed fiber reinforced polymers

401

(1)

5.5. Damage localization

401

(4)

5.6. Conclusion

405

(1)

5.7. References

405

(6)

Chapter 6. Low Frequency Electromagnetic Techniques

411

(52)

Michel LEMISTRE

6.1. Introduction

411

(1)

6.2. Theoretical considerations on electromagnetic theory

412

(14)

6.2.1. Maxwell's equations

412

(1)

6.2.2. Dipole radiation

413

(3)

6.2.3. Surface impedance

416

(5)

6.2.4. Diffraction by a circular aperture

421

(2)

6.2.5. Eddy currents

423

(1)

6.2.6. Polarization of dielectrics

423

(3)

6.3. Applications to the NDE/NDT domain

426

(10)

6.3.1. Dielectric materials

426

(2)

6.3.2. Conductive materials

428

(4)

6.3.3. Hybrid method

432

(4)

6.4. Signal processing

436

(11)

6.4.1. Time-frequency transforms

436

(1)

6.4.2. The continuous wavelet transform

437

(2)

6.4.3. The discrete wavelet transform

439

(2)

6.4.4. Multiresolution

441

(2)

6.4.5. Denoising

443

(4)

6.5. Application to the SHM domain

447

(13)

6.5.1. General principles

447

(1)

6.5.2. Magnetic method

448

(2)

6.5.3. Electric method

450

(1)

6.5.4. Hybrid method

450

(10)

6.6. References

460

(3)

Chapter 7. Capacitive Methods for Structural Health Monitoring in Civil Engineering

463

(28)

Xavier DÉROBERT and Jean IAQUINTA

7.1. Introduction

463

(1)

7.2. The principle

464

(2)

7.3. Capacitance probe for cover concrete

466

(5)

7.3.1. Layout

466

(1)

7.3.2. Sensitivity

467

(2)

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

469

(2)

7.4. Application for external post-tensioned cables

471

(8)

7.4.1. Influence of the location of the cable

473

(1)

7.4.2. Effect of air and water layers

474

(2)

7.4.3. Small inclusions

476

(1)

7.4.4. Example of an actual measurement

477

(2)

7.5. Future work

479

(1)

7.6. Monitoring historical buildings

480

(8)

7.6.1. Capacitance probe for moisture monitoring

481

(1)

7.6.2. Environmental conditions

482

(1)

7.6.3. Study on a stone wall test site

483

(2)

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

485

(3)

7.7. Conclusion

488

(1)

7.8. Acknowledgements

488

(1)

7.9. References

489

(2)

Short Biographies of the Contributors

491

(2)

Index

493

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Structural Health Monitoring

Summary

Author Biography

Table of Contents

Supplemental Materials