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ksiazka tytuł: DYNAMIC LOAD IDENTIFICATION FOR STRUCTURAL HEALTH MONITORING autor: ŁUKASZ JANKOWSKI
DOSTAWA WYŁĄCZNIE NA TERYTORIUM POLSKI

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DYNAMIC LOAD IDENTIFICATION FOR STRUCTURAL HEALTH MONITORING

Wersja papierowa
Wydawnictwo: IPPT PAN
ISBN: 978-83-89687-74-6
Liczba stron: 280
Oprawa: Miękka
Wydanie: 2013 r.
Język: polski

Dostępność: dostępny
35,90 zł 32,30 zł

This book deals with the inverse problem of identification of dynamic loads and its applications for low frequency structural health monitoring (SHM). It collects and unifies the work performed by the author within the framework of three research projects either alone or together with the three Ph.D. students under his supervision or co-supervision. In particular: - The inverse linear problem of load identification is discussed in the practically important case of limited instrumentation. Various techniques for augmenting the missing information are described together with three complementary quantitative measures of optimum sensor placement. - A method for identification of dynamic loads in elastoplastic structures is developed, including sensitivity analysis of the response and gradient-based optimization. - The general methodology of the virtual distortion method (VDM) is used to represent various SHM problems in terms of a load identification problem. This includes - A methodology for virtual isolation of substructures for the purpose of local SHM. - A model-free (nonparametric and based on purely experimental data) methodology for identification of structural damages, modifications and inelastic impacts. - A unified approach to the problem of simultaneous identification of unknown excitations and structural damages. All presented approaches are tested and illustrated in numerical examples that use a realistic numerical noise level of at least 5% rms. Depending on laboratory constraints, experimental verification is performed in selected cases.

SPIS TREŚCI

1. Introduction
1.1 The inverse problem of load identification
1.2 Structural health monitoring and load identification
1.3 Numerical models and experimental setups
1.4 Scope of the work

2. Load identification in linear structures
2.1 Introduction
2.1.1 Overview of the problem
2.1.2 State-of-the-art
2.1.3 Aims and techniąues
2.2 Problem formulation
2.2.1 Impulse response matrices
2.2.2 Direct problem
2.2.3 Inverse problem
2.2.4 Practical considerations
2.3 Overdetermined case
2.4 Underdetermined case
2.4.1 Decomposition of excitation
2.4.2 Single-stage identification
2.5 Optimum sensor placement
2.5.1 Criterion of conditioning
2.5.2 Criterion of informativity
2.5.3 Compound criterion
2.6 Numerical example
2.6.1 The structure
2.6.2 Optimum placement of sensors
2.6.3 Actual excitation
2.6.4 Identification results

3. Virtual distortion method
3.1 Introduction
3.1.1 Structural reanalysis
3.1.2 Overview of the VDM
3.1.3 Introductory examples
3.1.4 VDM and load identification
3.2 Distortions of a finite element
3.2.1 Basis distortions and equivalent element loads
3.2.2 Total distortions
3.2.3 Decomposition of global elastic forces
3.2.4 Equation of motion of the original structure
3.3 Direct problem
3.3.1 Structural modifications and damages
3.3.2 Pseudo loads and virtual distortions
3.3.3 Solution scheme
3.3.4 Time discretization
3.4 Inverse problem
3.4.1 Objective function
3.4.2 Sensitivity analysis
3.4.3 Time discretization

4. Model-free structural health monitoring
4.1 State-of-the-art and introduction
4.2 Timc-domain formulation
4.2.1 The direct problem
4.2.2 The inversc problem
4.2.3 Time discretization and numerical solution
4.3 Frequency-domain formulation
4.3.1 The direct problem
4.3.2 The iiwerse problem
4.3.3 FFT and windowing function
4.4 Identification of inelastic impacts
4.4.1 The direct problem
4.4.2 The iiwerse problem
4.5 Selected experimental results
4.5.1 The structure
4.5.2 Excitations and measurements
4.5.3 Single nodal mass modification
4.5.4 Modification of two nodal masscs

5. Virtual isolation of substructures for local health monitoring
5.1 Motivation
5.2 State-of-the-art
5.2.1 Static case
5.2.2 Dynamie case
5 2.3 Substructure separation methods
5.3 Overview of the isolation method
5.3.1 Two-stage monitoring
5.3.2 Excitations, sensors and measured responses
5.3.3 Stage I: substructure isolation
5.3.4 Stage II: local identification
5.3.5 Substructure isolation and load identification
5.4 Isolation in time domain
5.4.1 Isolation with other types of virtual supports
5.4.2 Time discretization and numerical stability
5.5 Isolation in freąuency domain
5.5.1 Isolation in time domain vs. isolation in frequency domain
5.5.2 FFT of the tirne-domain responses
5.6 Numerical examples
5.6.1 2-DOF mass-spring system
5.6.2 6-DOF mass-spring system
5.7 Experimental verification
5.7.1 Experimental setup
5.7.2 Isolation and identification in time domain
5.7.3 Isolation and identification in frequency domain

6. Simultaneous identification of damages and dynamie excitations
6.1 State-of-the-art
6.2 Damage-equivalent excitations
6.2.1 VDM-based formulation and the direct problem
6.2.2 Off-line identification
6.2.3 Online identification
6.2.4 Numerical example
6.2.5 Experimental example
6.3 Parametrization of loads
6.3.1 Modeling of moving masses
6.3.2 Coupled modeling of moving masses and damages
6.3.3 Identification
6.3.4 Numerical example

7. Load identification in elastoplastic structures
7.1 Bilinear isotropic hardening plasticity
7.2 The direct problem
7.2.1 Continuous formulation
7.2.2 Discrete-time setting
7.3 The inverse problem
7.3.1 Objective function
7.3.2 First order sensitivity analysis
7.3.3 Approximate second order sensitivity analysis
7.4 Numerical example
7.4.1 The structure
7.4.2 Actual excitation and thc response
7.4.3 Sensor placement
7.4.4 Identification results

8. Conclusions
8.1 Original results
8.2 Further research

A. Linear inverse problem
A.1 Linear operators
A.1.1 Boundedness, continuity and compactness
A.1.2 Ill-posedness, ill-conditioning and regularization
A.2 Infinite dimensional integral problems
A.2.1 Linear integral operator
A.2.2 Linear integral eąuations
A.2.3 Discretization
A.3 Finite dimensional discretized probleins
A.3.1 Solvability and conditioning
A.3.2 Numerical regularization

Bibliography

 

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