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E-grāmata: Health Assessment of Engineered Structures: Bridges, Buildings and Other Infrastructures [World Scientific e-book]

Edited by (Univ Of Arizona, Usa)
  • Formāts: 352 pages
  • Izdošanas datums: 28-Jun-2013
  • Izdevniecība: World Scientific Publishing Co Pte Ltd
  • ISBN-13: 9789814439022
Citas grāmatas par šo tēmu:
  • World Scientific e-book
  • Cena: 136,18 €*
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Health Assessment of Engineered Structures: Bridges, Buildings and Other InfrastructuresPalielināt
  • Formāts: 352 pages
  • Izdošanas datums: 28-Jun-2013
  • Izdevniecība: World Scientific Publishing Co Pte Ltd
  • ISBN-13: 9789814439022
Citas grāmatas par šo tēmu:
World Scientific e-booksMore info about World Scientific e-books
Rokasgrāmatas mājas lapa: http://www.worldscientific.com/worldscibooks/10.1142/8628#t=toc
Civil engineers describe some of the major techniques for assessing the condition of structures, pointing out their merits, demerits, and future challenges. Among their topics are monitoring the structural health of civil infrastructure, stochastic filtering in structural health assessment, wavelet-based techniques for structural health monitoring, health diagnostics of highway bridges using vibration response data, and sensors used in structural health monitoring. Annotation ©2013 Book News, Inc., Portland, OR (booknews.com)

Health Assessment of Engineered Structures has become one of the most active research areas and attracted multi-disciplinary interest. Since available financial recourses are very limited, extending the life of existing bridges, buildings and other infrastructures has become a major challenge to the engineering profession world-wide. Some of the related areas are in the development phase. As the area matures, more new areas are being identified to implement the concept. The available information may not be available in an organized way for interested parties who are not expert in the area. This edited book will cover some of the most recent developments (theoretical, experimental, and application potentials) in structural health assessment areas. These areas are not matured enough to write book on them. Students (undergraduate and graduate), researchers (university and industrial), and practitioners (government and private) will be interested in the topics presented in the book. After discussing the general concept, various currently available methods of structural health assessment will be presented. A chapter also will discuss future directions in structural health assessment area since the area is evolving. Smart sensors are routinely used to assess structural health. Sensor types, platforms and data conditioning for practical applications will be presented. Wireless collection of sensor data, sensor power needs and on-site energy harvesting will be discussed. Uncertainty in the collected data will be extensively addressed. Long term monitoring of structures will also be presented. Each chapter will be authored by the most active scholar(s) in the area.
Preface v
Chapter 1 Structural Health Monitoring for Civil Infrastructure
1(32)
E.J. Cross
K. Worden
C.R. Farrar
1 Introduction: SHM Ideology
1(4)
1.1 The aims of SHM
2(1)
1.2 Potential benefits of SHM
3(1)
1.3 Disambiguation: what SHM is not
3(2)
2 SHM in Practice
5(8)
2.1 Instrumentation for SHM
6(2)
2.2 Assessment of structural condition from measurements
8(1)
2.2.1 Feature Extraction
8(1)
2.2.2 Pattern Recognition for inference on structural condition from features
9(1)
2.3 Validation of SHM systems
10(1)
2.4 Fundamental axioms of SHM
11(2)
3 Civil Infrastructure and SHM
13(2)
4 Benchmarks
15(6)
4.1 The I-40 Bridge
15(3)
4.2 The Steelquake Structure
18(2)
4.3 The Z24 Bridge
20(1)
5 Case Study: Z24 Bridge
21(5)
6 Continuing Challenges in SHM
26(7)
Acknowledgments
28(1)
References
28(5)
Chapter 2 Enhanced Damage Locating Vector Method for Structural Health Monitoring
33(24)
S. T. Quek
V. A. Tran
N. N. K. Lee
1 The DLV Method Introduction
33(2)
1.1 General concept
33(1)
1.2 Normalized cumulative energy (NCE)
34(1)
2 Identifying Actual Damage Elements
35(1)
2.1 Intersection scheme
35(1)
3 Formulation of Flexibility Matrix at Sensor Location
36(9)
3.1 Forming flexibility matrix using static responses
37(1)
3.1.1 Static responses with load of known magnitude
37(1)
3.1.2 Static responses with load of unknown magnitude
38(1)
3.2 Forming flexibility matrix using dynamic responses
39(1)
3.2.1 Dynamic responses with known excitation
40(3)
3.2.2 Dynamic responses with unknown excitation
43(2)
4 Lost Data Reconstruction for Wireless Sensors
45(1)
4.1 Lost data reconstruction algorithm
45(1)
5 Numerical and Experimental Examples
46(9)
5.1 Numerical example: 2-D warehouse frame structure
47(4)
5.2 Experimental example: 3-D modular truss structure
51(4)
6 Concluding Remarks
55(2)
References
56(1)
Chapter 3 Dynamics-based Damage Identification
57(26)
Pizhong Qiao
Wei Fan
1 Introduction
57(3)
2 Damage Identification Algorithms
60(8)
2.1 Literature review
60(2)
2.2 Two-dimensional Gapped Smoothing Method (GSM)
62(2)
2.3 Strain Energy-based Damage Index Method (DIM)
64(2)
2.4 Uniform Load Surface (ULS)
66(1)
2.5 Generalized Fractal Dimension (GFD)
67(1)
3 Comparative Study
68(11)
3.1 Geometry of the composite plate
68(1)
3.2 Numerical analysis
69(2)
3.3 Damage identification based on numerical data
71(3)
3.4 Experimental program
74(3)
3.5 Damage identification based on experimental data
77(2)
4 Summary and Conclusions
79(4)
Acknowledgements
80(1)
References
80(3)
Chapter 4 Simulation Based Methods for Model Updating in Structural Condition Assessment
83(30)
H. A. Nasrellah
B. Radhika
V. S. Sundar
C. S. Manohar
1 Introduction
83(3)
2 Statically loaded structures: MCMC based methods
86(4)
3 Dynamically loaded structures: sequential Monte Carlo approach
90(11)
3.1 Hidden state estimation
90(3)
3.2 Combined state and force identification
93(1)
3.3 Combined state and parameter estimation
94(1)
3.3.1 Method of augmented states and global iterations
95(1)
3.3.2 Method of maximum likelihood
96(2)
3.3.3 Bank of filter approach
98(2)
3.3.4 Combined MCMC and Bayesian filters
100(1)
3.4 Other classes of updating problems
100(1)
4 Finite element model updating with combined static and dynamic Measurements
101(5)
5 Closing remarks
106(7)
Acknowledgements
109(1)
References
109(4)
Chapter 5 Stochastic Filtering In Structural Health Assessment: Some Perspectives and Recent Trends
113(36)
S. Sarkar
T. Raveendran
D. Roy
R. M. Vasu
1 Introduction
113(4)
2 KF, EKF and EnKF
117(11)
2.1 A pseudo- dynamic approach
120(1)
2.2 A pseudo-dynamic EnKF (PD-EnKF)
121(3)
2.3 The PD-EnKF algorithm
124(2)
2.3.1 Numerical illustrations on elastography using PD-EnKF
126(2)
3 Particle Filters
128(16)
3.1 Conditional expectation
129(1)
3.2 Baye's formula
129(1)
3.3 Ito and Stratonovich integrals
130(2)
3.4 Kushner-Stratonovich equation
132(1)
3.5 Euler approximation
133(2)
3.6 Dynamic SSI using particle filters
135(2)
3.7 Bootstrap filter (BS)
137(2)
3.8 Semi-analytical particle filter (SAPF)
139(2)
3.8.1 Numerical examples
141(2)
3.9 Girsanov corrected particle filter
143(1)
4 Conclusions
144(5)
References
145(4)
Chapter 6 A Novel Health Assessment Method for Large Three Dimensional Structures
149(30)
Ajoy Kumar Das
Achintya Haldar
1 Introduction
149(2)
2 Concept of System Identification (SI)
151(1)
3 SHA Using Static Responses
151(1)
4 SHA Using Dynamic Responses
152(1)
5 Time-Domain SI-Based SHA Procedures
153(1)
6 Time-Domain SHA Procedures with Unknown Input (UI)
154(1)
7 The Kalman Filter Concepts and its Application for SHA
155(3)
8 Extension of GILS-EKF-UI for 3D Structures
158(7)
8.1 Stage 1 - concept of 3D GILS-UI
159(3)
8.2 Stage2 - concept of EKF-WGI
162(3)
9 Application Examples
165(8)
9.1 Example 1 - health assessment of a 3D frame
165(1)
9.1.1 Description of the frame
165(1)
9.1.2 Scaling of additional responses
166(1)
9.1.3 Health assessment of defect-free frame
167(1)
9.1.4 Health assessment of defective frames
168(2)
9.2 Example 2 - health assessment of a 3D truss-frame
170(1)
9.2.1 Description of the truss-frame
170(2)
9.2.2 Health assessment of defect-free truss-frame
172(1)
9.2.3 Health assessment of defective truss-frames
172(1)
10 Conclusions
173(6)
Acknowledgements
174(1)
References
175(4)
Chapter 7 Wavelet-Based Techniques for Structural Health Monitoring
179(24)
Z. Hou
A. Hera
M. Noori
1 Introduction
179(1)
2 Brief Background of Wavelet-Based Methodologies for Damage Detection
180(2)
3 Damage Detection Using Simulation Data for a Simple Structural Model
182(4)
4 Wavelet approach for ASCE SHM benchmark study data
186(3)
5 SHM by the wavelet-packet based sifting process
189(10)
5.1 Wavelet Packet (WP) Decomposition
189(2)
5.2 Instantaneous Modal parameters
191(1)
5.3 Numerical validation
192(2)
5.4 SHM application of the wavelet packet decomposition
194(3)
5.5 Confidence index for measurement data
197(2)
6 Concluding remarks
199(4)
Acknowledgement
199(1)
References
199(4)
Chapter 8 The HHT Based Structural Health Monitoring
203(38)
Norden E. Huang
Liming W. Salvino
Ya-Yu Nieh
Gang Wang
Xianyao Chen
1 Introduction
203(3)
2 Time-Frequency analysis
206(9)
2.1 The chirp data
210(1)
2.2 Speech signal analysis
211(1)
2.3 Comparisons amongst HHT, Wigner-Ville and Wavelet analysis
212(3)
3 Degree of Nonlinearity
215(5)
4 Numerical Model
220(5)
5 Bridge Structure Health Monitoring
225(5)
6 Ship Structure: Damping Spectral
230(3)
7 Aircraft Structure
233(4)
8 Conclusions
237(4)
Acknowledgments
238(1)
References
238(3)
Chapter 9 The Use of Genetic Algorithms for Structural Identification and Damage Assessment
241(28)
C. G. Koh
Z. Zhang
1 Introduction
241(2)
2 Definition of the Problem: System Identification Using Genetic Algorithms
243(1)
3 Characteristics of Structural Identification As An Optimization Problem
244(6)
3.1 Effect of measurement noise
246(2)
3.2 Effects of recorded data length and using measurement from multiple load cases
248(2)
4 Uniformly Sampled Genetic Algorithm with Gradient Search
250(9)
4.1 Global search by USGA method
251(1)
4.1.1 Sampling methods
252(2)
4.1.2 Treatment after sampling
254(1)
4.1.2.1 Relaxation
254(1)
4.1.2.2 Perturbation
255(1)
4.1.2.3 Jump-back
256(1)
4.2 Local search by gradient based and non-gradient based methods
257(2)
5 Numerical Examples
259(3)
5.1 10-DOF Lumped Mass System
260(1)
5.2 Truss of 29 Elements and 28 DOFs
260(2)
6 Experimental Verification
262(2)
7 Conclusions
264(5)
References
265(4)
Chapter 10 Health Diagnostics of Highway Bridges Using Vibration Response Data
269(26)
Maria Q. Feng
Hugo C. Gomez
Andrea Zampieri
1 Introduction
269(1)
2 Methods for Structural Health Diagnostics
270(11)
2.1 Modal identification
273(1)
2.1.1 Output-only modal identification
273(2)
2.1.2 Input-output modal identification
275(1)
2.2 Identification of structural parameters
276(1)
2.2.1 Bayesian updating
276(2)
2.2.2 Optimization-based FE model updating
278(2)
2.2.3 Artificial neural networks
280(1)
3 Validation of Health Diagnostics Methods through Large---Scale Seismic Shaking Table Tests
281(3)
3.1 Test specimen, instrumentation and procedure
281(1)
3.2 Modal identification
282(1)
3.3 Damage assessment
283(1)
4 Applications in Long-Term Monitoring of Bridge Structures
284(11)
4.1 Use of ambient and traffic-induced vibration data
285(1)
4.1.1 Monitoring of natural frequencies
285(2)
4.1.2 Monitoring of mode shapes
287(2)
4.1.3 Monitoring of structural stiffness
289(1)
4.1.4 Health diagnostics
289(1)
4.2 Use of Seismic Acceleration Records
290(1)
References
291(4)
Chapter 11 Sensors Used in Structural Health Monitoring
295(16)
Mehdi Modares
Jamshid Mohammadi
1 Introduction
295(1)
2 Traditional Structural Health Monitoring
296(1)
3 Strain Sensors
296(1)
3.1 Foil strain gage
296(1)
3.2 Semiconductor strain gage
297(1)
4 Accelerometers
297(1)
4.1 Piezoelectric accelerometers
298(1)
4.2 Micro electro-mechanical systems (MEMS) accelerometers
298(1)
5 Displacement Sensors
298(1)
5.1 Linear variable differential transformer (LVDT)
299(1)
5.2 Global positioning system (GPS)
299(1)
6 Photographic and Video Image Devices
299(1)
6.1 Charge-coupled-devices
300(1)
7 Fiber Optic Sensors
300(2)
7.1 Fiber bragg grating sensors
301(1)
7.2 Distributed brillouin sensors
301(1)
7.3 Ramon distributed sensors
301(1)
8 Ultrasound Waves
302(1)
9 Laser Scanning
302(1)
9.1 Terrestrial laser scanning
302(1)
9.2 Laser doppler vibrometer
303(1)
10 Temperature sensors
303(1)
10.1 Thermocouples
303(1)
10.2 Resistance temperature detector
304(1)
10.3 Thermography
304(1)
11 Load Cells
304(1)
12 Anemoscopes
304(1)
13 Fatigue Sensors
305(1)
14 Summary Table for Sensors
305(6)
Acknowledgment
305(3)
References
308(3)
Chapter 12 Sensor Data Wireless Communication, Sensor Power Needs, and Energy Harvesting
311(14)
Erdal Oruklu
Jafar Saniie
Mehdi Modares
Jamshid Mohammadi
1 Introduction
311(2)
2 Structural Health Monitoring using Smart Acoustic Emission Sensors
313(4)
2.1 AE sensing methodology
315(2)
3 Wireless Sensor Networks for Structural Monitoring
317(2)
4 System-on-Chip Design for Smart Sensor Nodes
319(1)
5 Sustainable Operation of the Wireless Sensor Network
320(4)
5.1 Power consumption in structural health monitoring applications
321(1)
5.2 Energy harvesting
322(1)
5.3 Power management
323(1)
6 Further Information
324(1)
7 Concluding Remarks
324(1)
References 325(4)
Index 329
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