Cover image for Health Assessment of Engineered Structures : Bridges, Buildings and Other Infrastructures.
Health Assessment of Engineered Structures : Bridges, Buildings and Other Infrastructures.
Title:
Health Assessment of Engineered Structures : Bridges, Buildings and Other Infrastructures.
Author:
Haldar, Achintya.
ISBN:
9789814439022
Personal Author:
Physical Description:
1 online resource (352 pages)
Contents:
Contents -- Preface -- Chapter 1. Structural Health Monitoring for Civil Infrastructure E.J. Cross, K. Worden and C.R. Farrar -- 1. Introduction: SHM Ideology -- 1.1. The aims of SHM -- 1.2. Potential benefits of SHM -- 1.3. Disambiguation: what SHM is not -- 2. SHM in Practice -- 2.1. Instrumentation for SHM -- 2.2. Assessment of structural condition from measurements -- 2.2.1. Feature Extraction -- 2.2.2. Pattern Recognition for inference on structural condition from features -- 2.3. Validation of SHM systems -- 2.4. Fundamental axioms of SHM -- 3. Civil Infrastructure and SHM -- 4. Benchmarks -- 4.1. The I-40 Bridge -- 4.2. The Steelquake Structure -- 4.3. The Z24 Bridge -- 5. Case Study: Z24 Bridge -- 6. Continuing Challenges in SHM -- Acknowledgments -- References -- Chapter 2. Enhanced Damage Locating Vector Method for Structural Health Monitoring S. T. Quek, V. A. Tran, and N. N. K. Lee -- 1. The DLV Method Introduction -- 1.1. General concept -- 1.2. Normalized cumulative energy (NCE) -- 2. Identifying Actual Damage Elements -- 2.1. Intersection scheme -- 3. Formulation of Flexibility Matrix at Sensor Location -- 3.1. Forming flexibility matrix using static responses -- 3.1.1. Static responses with load of known magnitude -- 3.1.2. Static responses with load of unknown magnitude -- 3.2. Forming flexibility matrix using dynamic responses -- 3.2.1. Dynamic responses with known excitation -- 3.2.2. Dynamic responses with unknown excitation -- 4. Lost Data Reconstruction for Wireless Sensors -- 4.1. Lost data reconstruction algorithm -- 5. Numerical and Experimental Examples -- 5.1. Numerical example: 2-D warehouse frame structure -- 5.2. Experimental example: 3-D modular truss structure -- 6. Concluding Remarks -- References -- Chapter 3. Dynamics-based Damage Identification Pizhong Qiao and Wei Fan -- 1. Introduction.

2. Damage Identification Algorithms -- 2.1 Literature review -- 2.2 Two-dimensional Gapped Smoothing Method (GSM) -- 2.3 Strain Energy-based Damage Index Method (DIM) -- 2.4 Uniform Load Surface (ULS) -- 2.5 Generalized Fractal Dimension (GFD) -- 3. Comparative Study -- 3.1 Geometry of the composite plate -- 3.2 Numerical analysis -- 3.3 Damage identification based on numerical data -- 3.4 Experimental program -- 3.5 Damage identification based on experimental data -- 4. Summary and Conclusions -- Acknowledgements -- References -- Chapter 4. Simulation Based Methods for Model Updating in Structural Condition Assessment H. A. Nasrellah, B. Radhika, V. S. Sundar, and C. S. Manohar -- 1. Introduction -- 2. Statically loaded structures: MCMC based methods -- 3. Dynamically loaded structures: sequential Monte Carlo approach -- 3.1 Hidden state estimation -- 3.2 Combined state and force identification -- 3.3 Combined state and parameter estimation -- 3.3.1 Method of augmented states and global iterations -- 3.3.2 Method of maximum likelihood -- 3.3.3 Bank of filter approach -- 3.3.4 Combined MCMC and Bayesian filters -- 3.4 Other classes of updating problems -- 4. Finite element model updating with combined static and dynamic Measurements -- 5. Closing remarks -- Acknowledgements -- References -- Chapter 5. Stochastic Filtering In Structural Health Assessment: Some Perspectives and Recent Trends S. Sarkar, T. Raveendran, D. Roy, and R. M. Vasu -- 1. Introduction -- 2. KF, EKF and EnKF -- 2.1. A pseudo- dynamic approach -- 2.2. A pseudo-dynamic EnKF (PD-EnKF) -- 2.3. The PD-EnKF algorithm -- 2.3.1. Numerical illustrations on elastography using PD-EnKF -- 3. Particle Filters -- 3.1. Conditional expectation -- 3.2. Baye's formula -- 3.3. Ito and Stratonovich integrals -- 3.4. Kushner-Stratonovich equation -- 3.5. Euler approximation.

3.6. Dynamic SSI using particle filters -- 3.7. Bootstrap filter (BS) -- 3.8. Semi-analytical particle filter (SAPF) -- 3.8.1. Numerical examples -- 3.9. Girsanov corrected particle filter -- 4. Conclusions -- References -- Chapter 6. A Novel Health Assessment Method for Large Three Dimensional Structures Ajoy Kumar Das and Achintya Haldar -- 1. Introduction -- 2. Concept of System Identification (SI) -- 3. SHA Using Static Responses -- 4. SHA Using Dynamic Responses -- 5. Time-Domain SI-Based SHA Procedures -- 6. Time-Domain SHA Procedures with Unknown Input (UI) -- 7. The Kalman Filter Concepts and its Application for SHA -- 8. Extension of GILS-EKF-UI for 3D Structures -- 8.1. Stage 1 - concept of 3D GILS-UI -- 8.2. Stage2 - concept of EKF-WGI -- 9. Application Examples -- 9.1. Example 1 - health assessment of a 3D frame -- 9.1.1. Description of the frame -- 9.1.2. Scaling of additional responses -- 9.1.3. Health assessment of defect-free frame -- 9.1.4. Health assessment of defective frames -- 9.2. Example 2 - health assessment of a 3D truss-frame -- 9.2.1. Description of the truss-frame -- 9.2.2. Health assessment of defect-free truss-frame -- 9.2.3. Health assessment of defective truss-frames -- 10. Conclusions -- Acknowledgements -- References -- Chapter 7. Wavelet-Based Techniques for Structural Health Monitoring Z. Hou, A. Hera, and M. Noori -- 1. Introduction -- 2. Brief Background of Wavelet-Based Methodologies for Damage Detection -- 3. Damage Detection Using Simulation Data for a Simple Structural Model -- 4. Wavelet approach for ASCE SHM benchmark study data -- 5. SHM by the wavelet-packet based sifting process -- 5.1 Wavelet Packet (WP) Decomposition -- 5.2 Instantaneous Modal parameters -- 5.3 Numerical validation -- 5.4 SHM application of the wavelet packet decomposition -- 5.5 Confidence index for measurement data.

6. Concluding remarks -- Acknowledgement -- References -- Chapter 8. The HHT Based Structural Health Monitoring Norden E. Huang, Liming W. Salvino, Ya-Yu Nieh, Gang Wang and Xianyao Chen -- 1. Introduction -- 2. Time-Frequency analysis -- 2.1. The chirp data -- 2.2. Speech signal analysis -- 2.3. Comparisons amongst HHT, Wigner-Ville and Wavelet analysis -- 3. Degree of Nonlinearity -- 4. Numerical Model -- 5. Bridge Structure Health Monitoring -- 6. Ship Structure: Damping Spectral -- 7. Aircraft Structure -- 8. Conclusions -- Acknowledgments -- References -- Chapter 9. The Use of Genetic Algorithms for Structural Identification and Damage Assessment C. G. Koh and Z. Zhang -- 1. Introduction -- 2. Definition of the Problem: System Identification Using Genetic Algorithms -- 3. Characteristics of Structural Identification As An Optimization Problem -- 3.1 Effect of measurement noise -- 3.2 Effects of recorded data length and using measurement from multiple load cases -- 4. Uniformly Sampled Genetic Algorithm with Gradient Search -- 4.1 Global search by USGA method -- 4.1.1 Sampling methods -- 4.1.2 Treatment after sampling -- 4.1.2.1 Relaxation -- 4.1.2.2 Perturbation -- 4.1.2.3 Jump-back -- 4.2 Local search by gradient based and non-gradient based methods -- 5. Numerical Examples -- 5.1 10-DOF Lumped Mass System -- 5.2 Truss of 29 Elements and 28 DOFs -- 6. Experimental Verification -- 7. Conclusions -- References -- Chapter 10. Health Diagnostics of Highway Bridges Using Vibration Response Data Maria Q. Feng, Hugo C. Gomez, and Andrea Zampieri -- 1. Introduction -- 2. Methods for Structural Health Diagnostics -- 2.1 Modal identification -- 2.1.1 Output-only modal identification -- 2.1.2 Input-output modal identification -- 2.2 Identification of structural parameters -- 2.2.1 Bayesian updating -- 2.2.2 Optimization-based FE model updating.

2.2.3 Artificial neural networks -- 3. Validation of Health Diagnostics Methods through Large-Scale Seismic Shaking Table Tests -- 3.1 Test specimen, instrumentation and procedure -- 3.2 Modal identification -- 3.3 Damage assessment -- 4. Applications in Long-Term Monitoring of Bridge Structures -- 4.1 Use of ambient and traffic-induced vibration data -- 4.1.1 Monitoring of natural frequencies -- 4.1.2 Monitoring of mode shapes -- 4.1.3 Monitoring of structural stiffness -- 4.1.4 Health diagnostics -- 4.2 Use of Seismic Acceleration Records -- 5. Conclusions -- References -- Chapter 11. Sensors Used in Structural Health Monitoring Mehdi Modares and Jamshid Mohammadi -- 1. Introduction -- 2. Traditional Structural Health Monitoring -- 3. Strain Sensors -- 3.1. Foil strain gage -- 3.2. Semiconductor strain gage -- 4. Accelerometers -- 4.1. Piezoelectric accelerometers -- 4.2. Micro electro-mechanical systems (MEMS) accelerometers -- 5. Displacement Sensors -- 5.1. Linear variable differential transformer (LVDT) -- 5.2. Global positioning system (GPS) -- 6. Photographic and Video Image Devices -- 6.1. Charge-coupled-devices -- 7. Fiber Optic Sensors -- 7.1. Fiber bragg grating sensors -- 7.2. Distributed brillouin sensors -- 7.3. Ramon distributed sensors -- 8. Ultrasound Waves -- 9. Laser Scanning -- 9.1. Terrestrial laser scanning -- 9.2. Laser doppler vibrometer -- 10. Temperature sensors -- 10.1. Thermocouples -- 10.2. Resistance temperature detector -- 10.3. Thermography -- 11. Load Cells -- 12. Anemoscopes -- 13. Fatigue Sensors -- 14. Summary Table for Sensors -- Acknowledgment -- References -- Chapter 12. Sensor Data Wireless Communication, Sensor Power Needs, and Energy Harvesting Erdal Oruklu, Jafar Saniie, Mehdi Modares, and Jamshid Mohammadi -- 1. Introduction -- 2. Structural Health Monitoring using Smart Acoustic Emission Sensors.

2.1. AE sensing methodology.
Abstract:
Health Assessment of Engineered Structures has become one of the most active research areas and has attracted multi-disciplinary interest. Since available financial recourses are very limited, extending the lifespan of existing bridges, buildings and other infrastructures has become a major challenge to the engineering profession world-wide. Some of its related areas are only in their development phase. As the study of structural health assessment matures, more new areas are being identified to complement the concept. This book covers some of the most recent developments (theoretical and experimental) and application potentials in structural health assessment. It is designed to present currently available information in an organised form to interested parties who are not experts in the subject. Each chapter is authored by the most active scholar(s) in the area. After discussing the general concept, various currently available methods of structural health assessment (such as the use of smart sensors) are presented. Health Assessment discusses the following: sensor types, platforms and data conditioning for practical applications; wireless collection of sensor data, sensor power needs and on-site energy harvesting; and long term monitoring of structures. Uncertainty in collected data is also extensively addressed. A chapter discussing future directions in structural health assessment is also included.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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