LEADER 05617nam 22007574a 450 001 9911019394503321 005 20200520144314.0 010 $a1-280-51053-6 010 $a9786610510535 010 $a1-84704-451-4 010 $a0-470-61207-X 010 $a0-470-39440-4 010 $a1-84704-551-0 035 $a(CKB)1000000000335570 035 $a(EBL)700719 035 $a(SSID)ssj0000252593 035 $a(PQKBManifestationID)11244229 035 $a(PQKBTitleCode)TC0000252593 035 $a(PQKBWorkID)10181096 035 $a(PQKB)10358554 035 $a(MiAaPQ)EBC700719 035 $a(MiAaPQ)EBC261388 035 $a(Au-PeEL)EBL261388 035 $a(CaONFJC)MIL51053 035 $a(OCoLC)501312931 035 $a(EXLCZ)991000000000335570 100 $a20051121d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aStructural health monitoring /$fedited by Daniel Balageas, Claus-Peter Fritzen and Alfredo Guemes 210 $aLondon ;$aNewport Beach, CA $cISTE$d2006 215 $a1 online resource (497 p.) 225 1 $aISTE ;$vv.90 300 $aDescription based upon print version of record. 311 $a1-905209-01-0 320 $aIncludes bibliographical references and index. 327 $aStructural Health Monitoring; Table of Contents; Foreword; Chapter 1. Introduction to Structural Health Monitoring; 1.1. Definition of Structural Health Monitoring; 1.2. Motivation for Structural Health Monitoring; 1.3. Structural Health Monitoring as a way of making materials and structures smart; 1.4. SHM and biomimetics; 1.5. Process and pre-usage monitoring as a part of SHM; 1.6. SHM as a part of system management; 1.7. Passive and active SHM; 1.8. NDE, SHM and NDECS; 1.9. Variety and multidisciplinarity: the most remarkable characters of SHM 327 $a1.10. Birth of the Structural Health Monitoring Community1.11. Conclusion; 1.12. References; Chapter 2. Vibration-Based Techniques for Structural Health Monitoring; 2.1. Introduction; 2.2. Basic vibration concepts for SHM; 2.2.1. Local and global methods; 2.2.2. Damage diagnosis as an inverse problem; 2.2.3. Model-based damage assessment; 2.3. Mathematical description of structural systems with damage; 2.3.1. General dynamic behavior; 2.3.2. State-space description of mechanical systems; 2.3.3. Modeling of damaged structural elements; 2.4. Linking experimental and analytical data 327 $a2.4.1. Modal Assurance Criterion (MAC) for mode pairing2.4.2. Modal Scaling Factor (MSF); 2.4.3. Co-ordinate Modal Assurance Criterion (COMAC); 2.4.4. Damping; 2.4.5. Expansion and reduction; 2.4.6. Updating of the initial model; 2.5. Damage localization and quantification; 2.5.1. Change of the flexibility matrix; 2.5.2. Change of the stiffness matrix; 2.5.3. Strain-energy-based indicator methods and curvature modes; 2.5.4. MECE error localization technique; 2.5.5. Static displacement method; 2.5.6. Inverse eigensensitivity method; 2.5.7. Modal force residual method 327 $a2.5.8. Kinetic and strain energy-based sensitivity methods2.5.9. Forced vibrations and frequency response functions; 2.6. Solution of the equation system; 2.6.1. Regularization; 2.6.2. Parameter subset selection; 2.6.3. Other solution methods; 2.6.4. Variances of the parameters; 2.7. Neural network approach to SHM; 2.7.1. The basic idea of neural networks; 2.7.2. Neural networks in damage detection, localization and quantification; 2.7.3. Multi-layer Perceptron (MLP); 2.8. A simulation example; 2.8.1. Description of the structure; 2.8.2. Application of damage indicator methods 327 $a2.8.3. Application of the modal force residual method and inverse eigensensitivity method2.8.4. Application of the kinetic and modal strain energy methods; 2.8.5. Application of the Multi-Layer Perceptron neural network; 2.9. Time-domain damage detection methods for linear systems; 2.9.1. Parity equation method; 2.9.2. Kalman filters; 2.9.3. AR and ARX models; 2.10. Damage identification in non-linear systems; 2.10.1. Extended Kalman filter; 2.10.2. Localization of damage using filter banks; 2.10.3. A simulation study on a beam with opening and closing crack; 2.11. Applications 327 $a2.11.1. I-40 bridge 330 $aThis book is organized around the various sensing techniques used to achieve structural health monitoring. Its main focus is on sensors, signal and data reduction methods and inverse techniques, which enable the identification of the physical parameters, affected by the presence of the damage, on which a diagnostic is established. Structural Health Monitoring is not oriented by the type of applications or linked to special classes of problems, but rather presents broader families of techniques: vibration and modal analysis; optical fibre sensing; acousto-ultrasonics, using piezoelectr 410 0$aISTE 606 $aStructural health monitoring 606 $aStructural analysis (Engineering) 606 $aAutomatic data collection systems 606 $aDetectors 615 0$aStructural health monitoring. 615 0$aStructural analysis (Engineering) 615 0$aAutomatic data collection systems. 615 0$aDetectors. 676 $a624.1/71 701 $aBalageas$b Daniel$0149376 701 $aFritzen$b Claus-Peter$0953146 701 $aGuemes$b Alfredo$0953147 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019394503321 996 $aStructural health monitoring$92154805 997 $aUNINA