摘要 | 第4-5页 |
Abstract | 第5页 |
Chapter 1 Introduction | 第9-21页 |
1.1 Importance of structural damage identification and structural health monitoring | 第9-10页 |
1.2 Research background | 第10-11页 |
1.3 State of the art of damage identification methods | 第11-14页 |
1.3.1 Natural frequency based methods | 第12-13页 |
1.3.2 Mode shape based methods | 第13页 |
1.3.3 Flexibility matrix based methods | 第13页 |
1.3.4 Stiffness matrix based methods | 第13-14页 |
1.3.5 Other methods | 第14页 |
1.4 Development of damage identification based on wavelet transform | 第14-17页 |
1.5 Introduction of distributed long-gage fiber optic sensors used in this research | 第17-18页 |
1.6 Research work and structure of this thesis | 第18-21页 |
Chapter 2 Theoretical basis | 第21-49页 |
2.1 How wavelet transform is introduced | 第21-27页 |
2.1.1 Applications of Fourier transform | 第21-24页 |
2.1.2 Applications of wavelet transform | 第24-27页 |
2.2 Fourier transform | 第27-31页 |
2.2.1 Fourier series | 第28-29页 |
2.2.2 Continuous Fourier transform | 第29-30页 |
2.2.3 Comparison between Fourier transform and Fourier series | 第30页 |
2.2.4 Discrete Fourier transform | 第30-31页 |
2.3 Short time Fourier transform | 第31-34页 |
2.3.1 Heisenberg uncertainty principle | 第32-33页 |
2.3.2 Resolutions of the STFT | 第33-34页 |
2.4 Continuous wavelet transform | 第34-38页 |
2.4.1 Conditions on mother wavelets | 第37页 |
2.4.2 Resolutions of wavelet transform | 第37-38页 |
2.5 Discrete wavelet transform | 第38-39页 |
2.6 Wavelet packet transform | 第39-41页 |
2.7 Wavelet properties | 第41-42页 |
2.8 Singularity detection principle of wavelet transform | 第42-45页 |
2.8.1 In displacement and acceleration data analysis | 第42-44页 |
2.8.2 In strain time-history signals | 第44-45页 |
2.9 Noise effects | 第45-47页 |
2.9.1 Wavelet based denoising | 第45-46页 |
2.9.2 Simulation of noise | 第46-47页 |
2.10 Conclusions | 第47-49页 |
Chapter 3 Damage Identification based on modal displacement | 第49-71页 |
3.1 Wavelet selection | 第49-50页 |
3.1.1 Signal analysis | 第49-50页 |
3.1.2 Wavelet properties | 第50页 |
3.2 Finite element analysis | 第50-55页 |
3.2.1 Numerical Mmodel | 第51-54页 |
3.2.2 Damage scenarios | 第54-55页 |
3.3 Data processing | 第55-66页 |
3.3.1 Boundary effect problem | 第55-57页 |
3.3.2 Comparison between deflection shape and displacement mode shape | 第57-59页 |
3.3.3 Comparison of different wavelets | 第59-61页 |
3.3.4 Selection of deflection mode shape level | 第61-63页 |
3.3.5 Detecting damages by using CWT and selection of the best level for DWT | 第63-64页 |
3.2.6 Multiple damages locations and severities | 第64-65页 |
3.2.7 Calculated deflection mode shape | 第65-66页 |
3.4 Damage identification process | 第66-67页 |
3.5 Validation by scaled gantry crane model | 第67-69页 |
3.6 Conclusions | 第69-71页 |
Chapter 4 Damage detection based on modified Wavelet Packet Energy Rate | 第71-89页 |
4.1 Wavelet selection | 第72-73页 |
4.1.1 Signal analysis | 第72-73页 |
4.1.2 Wavelet properties | 第73页 |
4.2 Finite element analysis | 第73-76页 |
4.2.1 Nume rical model | 第73-75页 |
4.2.2 Damage Scenarios | 第75-76页 |
4.3 Data Processing | 第76-84页 |
4.3.1 Comparison of the proposed damage index and conventional indexes | 第76-77页 |
4.3.2 Comparison between hammer excitation and running car excitation | 第77-79页 |
4.3.3 Detectability of damages on simply supported beam | 第79-80页 |
4.3.4 Detectability of multiple damages on the main beam and damage on the column | 第80页 |
4.3.5 Verification of noise effect on the proposed method | 第80-82页 |
4.3.6 Effects of stiffness loss level | 第82页 |
4.3.7 Effects of damage location | 第82-83页 |
4.3.8 Consideration of both damage location and damage level | 第83-84页 |
4.4 Damage identification process | 第84-85页 |
4.5 Validation by scaled gantry crane model | 第85-86页 |
4.6 Conclusions | 第86-89页 |
Chapter 5 Experiment on a steel beam | 第89-95页 |
5.1 Design of the experiment | 第89-90页 |
5.2 Eexperiment process | 第90-92页 |
5.3 Damage identification based on the data acquired by the experimental steel beam | 第92-95页 |
Chapter 6 Conclusions | 第95-97页 |
References | 第97-101页 |
Acknowledgements | 第101-102页 |
Papers published during master degree | 第102页 |