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E-raamat: Vibration Testing and Applications in System Identification of Civil Engineering Structures

(City University of Hong Kong), (Tongji University, China)
  • Formaat: 424 pages
  • Ilmumisaeg: 06-Sep-2022
  • Kirjastus: CRC Press
  • ISBN-13: 9780429819971
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Vibration Testing and Applications in System Identification of Civil Engineering StructuresSuurem pilt
  • Formaat: 424 pages
  • Ilmumisaeg: 06-Sep-2022
  • Kirjastus: CRC Press
  • ISBN-13: 9780429819971
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This book covers vibration testing and identification of dynamic structural systems. It starts from the fundamentals of structural dynamics, and covers the methods of modal analysis and model identification, vibration tests and the related experimental setup. It concludes with an outline of the authors software, demonstrating practical applications, and illustrated with real-world case studies of full-scale structures.

Theory is presented and derived step-by-step, with a detailed measurement system developed for vibration tests. This book is written for Masters students and enables them to understand the theories of system identification and empowers them to apply this in practice.
Preface xi
Acknowledgments xiii
Authors xvii
1 Introduction
1(28)
1.1 Fundamentals of structural vibration tests
1(9)
1.1.1 Free vibration test
4(1)
1.1.2 Forced vibration test
5(3)
1.1.3 Ambient vibration test
8(2)
1.2 Why are structural vibration tests needed?
10(6)
1.2.1 Building vibration
10(1)
1.2.2 Bridge vibration
11(1)
1.2.3 Determination of cable tension of long-span bridges
12(3)
1.2.4 Train-induced vibration
15(1)
1.3 What is system identification?
16(8)
1.3.1 Modal system identification---modal analysis
17(2)
1.3.2 Structural system identification---model updating
19(3)
1.3.3 Structural health monitoring
22(2)
1.4 How to use this book
24(5)
1.4.1 Part 1: Background knowledge
24(1)
1.4.2 Part 2: Modal analysis
25(1)
1.4.3 Part 3: Model updating
25(1)
References
26(3)
2 Fundamentals of structural dynamics
29(116)
2.1 Single-degree-of-freedom systems
29(65)
2.1.1 Undamped free vibration
31(6)
2.1.2 Damped free vibration
37(1)
2.1.2.1 Under-damped free vibration
38(6)
2.1.2.2 Critically damped free response
44(2)
2.1.2.3 Over-damped free response
46(3)
2.1.3 Forced vibration: harmonic excitation
49(4)
2.1.3.1 Dynamic multiplication factor
53(2)
2.1.3.2 Estimation of damping ratio
55(4)
2.1.3.3 Resonance
59(3)
2.1.4 Forced vibration: general force
62(1)
2.1.4.1 Response to unit impulse
62(2)
2.1.4.2 Duhamel's integral
64(1)
2.1.4.3 Numerical method for forced vibration
65(19)
2.1.4.4 Earthquake excitation
84(3)
2.1.5 Fast response calculation based on Duhamel's integral
87(1)
2.1.5.1 Acceleration algorithm
87(7)
2.2 Multi-degree-of-freedom systems
94(51)
2.2.1 Shear building model---a multi-DOF system
94(10)
2.2.2 Undamped free vibration of a multi-DOF system
104(1)
2.2.2.1 Natural frequencies and mode shapes
104(14)
2.2.2.2 Time-domain responses of a multi-DOF system
118(3)
2.2.2.3 Orthogonal property of mode shapes
121(1)
2.2.2.4 Mode shape normalization
122(2)
2.2.3 Forced vibration of an undamped multi-DOF system
124(3)
2.2.4 Forced vibration of an under-damped multi-DOF system
127(1)
2.2.4.1 Rayleigh damping
128(1)
2.2.4.2 Caughey damping
129(15)
References
144(1)
3 Modal analysis based on power spectral density data
145(22)
3.1 Power spectral density
145(4)
3.2 Mathematical modeling of PSD
149(2)
3.3 The optimization algorithm
151(4)
3.3.1 The objective function
151(1)
3.3.2 Optimization for bm
152(1)
3.3.3 Optimization for Sm
152(1)
3.3.4 Initialization for the iteration
153(1)
3.3.5 The structure of the optimization algorithm
154(1)
3.4 Simulated study: a 12-story shear building model
155(2)
3.5 Experimental study: modal analysis of a coupled structural system
157(10)
References
166(1)
4 Modal analysis based on cross-correlation data
167(18)
4.1 Mathematical model of a structural dynamic system
167(6)
4.2 Identifying modal parameters
173(7)
4.2.1 Modal-component optimization
174(1)
4.2.1.1 Algorithm 4.1: Modal-component optimization
174(1)
4.2.2 Optimization of one modal component
175(1)
4.2.2.1 Mode shape
176(1)
4.2.2.2 Modal initial conditions
177(2)
4.2.2.3 Natural frequency and damping ratio
179(1)
4.2.2.4 Algorithm 4.2: Optimization of one modal component M(k)m
179(1)
4.3 Modal analysis of a footbridge
180(5)
References
183(2)
5 System identification based on vector autoregressive moving average models
185(34)
5.2 State-space representation of a dynamic system
185(4)
5.2 Transforming structural models to VAR models for free vibration
189(3)
5.3 Transforming structural models to VARMA models for forced vibration
192(6)
5.4 Extracting modal parameters from a VARMA model
198(5)
5.5 Identification of VAR models
203(3)
5.6 Illustrative example
206(1)
5.7 System identification of an office building
207(12)
5.7.1 Ambient vibration test
209(1)
5.7.2 Identifying the VAR model and modal parameters
210(6)
Appendix
216(1)
A.1 The vec operator and Kronecker product
216(2)
References
218(1)
6 Model updating by minimizing errors in modal parameters
219(142)
6.1 Basic formulation of model updating
219(28)
6.1.1 Parameterization of the model class
219(1)
6.1.2 Objective functions
220(4)
6.1.3 Numerical case study of a two-story shear building model: non-uniqueness problem
224(8)
6.1.4 Numerical case study of a simple beam: symmetrical problem
232(2)
6.1.5 Numerical case study of a truss: structural damage detection by model updating
234(1)
6.1.5.1 Modeling of the truss and cases considered
234(4)
6.1.5.2 Simulation of measured time-domain vibrations
238(2)
6.1.5.3 Identified modal parameters
240(1)
6.1.5.4 Model updating: Case UD
241(1)
6.1.5.5 Structural damage detection by model updating: Cases Dl and D2
241(2)
6.1.6 Determination of the weighting factors following the Bayesian approach
243(4)
6.2 Numerical optimization algorithms
247(48)
6.2.1 General formulation
248(2)
6.2.2 Uniqueness of optimization solution
250(3)
6.2.3 Single-variable unconstrained optimization
253(1)
6.2.3.1 Golden-section method
253(9)
6.2.3.2 Polynomial approximation method
262(3)
6.2.3.3 Iterative quadratic approximation method
265(4)
6.2.3.4 MATLAB function: Fminbnd()
269(2)
6.2.4 Multivariate unconstrained optimization
271(2)
6.2.4.1 Zero-order: Univariate search method
273(2)
6.2.4.2 Zero-order: Conjugate direction method
275(3)
6.2.4.3 First-order: Steepest descent method
278(1)
6.2.4.4 First-order: Conjugate gradient method
279(2)
6.2.4.5 Second-order: Newton--Raphson method
281(4)
6.2.4.6 MATLAB function: Fminsearch()
285(1)
6.2.5 Gradient and Hessian approximation using finite--difference
286(4)
6.2.6 Probabilistic optimization algorithms
290(1)
6.2.6.1 Random search
291(1)
6.2.6.2 Simulated annealing
292(3)
6.3 Case studies
295(66)
6.3.1 Model updating of a shear building model
295(1)
6.3.1.1 Description of the structure and cases considered
296(2)
6.3.1.2 Impact hammer test and identified modal parameters
298(7)
6.3.1.3 Modeling of the four-story shear building model
305(5)
6.3.1.4 Stiffness identification of the baseline structure (NoMass)
310(2)
6.3.1.5 Mass identification
312(3)
6.3.2 Joint damage detection of a two-story steel frame by model updating
315(2)
6.3.2.1 Description of the structure
317(2)
6.3.2.2 Modeling of the two-story steel frame
319(6)
6.3.2.3 Vibration test
325(2)
6.3.2.4 Modal identification
327(2)
6.3.2.5 Model updating of the undamaged structure
329(8)
6.3.2.6 Model updating in damage case DB
337(1)
6.3.2.7 Model updating in damage case AD
338(1)
6.3.3 Model updating of an old factory building
338(2)
6.3.3.1 Description of the building
340(3)
6.3.3.2 Field test and modal identification
343(6)
6.3.3.3 Modeling of the factory building
349(5)
6.3.3.4 Model updating utilizing measured modal parameters
354(5)
References
359(2)
7 Bayesian model updating based on Markov chain Monte Carlo
361(46)
7.1 Deterministic model based on the eigenvalue problem
361(2)
7.2 Deterministic model updating
363(4)
7.2.1 Model updating of a scaled transmission tower
364(3)
7.3 Bayesian updating: the posterior PDF
367(4)
7.4 Importance sampling
371(4)
7.5 Metropolis-Hastings algorithm
375(4)
7.5.1 Overview
375(1)
7.5.2 Convergence of the algorithm
376(3)
7.6 Bayesian updating using the MH algorithm and the eigenvalue problem error
379(6)
7.6.1 The proposal PDF
379(1)
7.6.1.1 Sampling for the first sample
379(1)
7.6.1.2 Sampling for a general sample
380(1)
7.6.2 The prediction-error variances
380(1)
7.6.3 Summary of the proposed algorithm
381(1)
7.6.4 Bayesian model updating of the shear building
382(3)
7.7 Bayesian model updating using a multi-level MCMC method
385(22)
7.7.1 The posterior PDF for the multi-level MCMC method
386(4)
7.7.2 The sampling scheme for the multi-level MCMC method
390(4)
7.7.3 Bayesian model updating of a transmission tower
394(5)
7.7.4 The posterior PDF based on the fractional errors of modal parameters
399(2)
7.7.5 Bayesian model updating of a coupled structural system
401(4)
References
405(2)
Index 407
Lam, Heung Fai is currently Associate Professor at Department of Architecture and Civil Engineering, City University of Hong Kong, and Associate Editor of Engineering Structures.

Yang, Jia-Hua is currently Associate Professor at College of Civil Engineering and Architecture and Scientific Research Center of Engineering Mechanics, Guangxi University (China).
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