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Reports List on Structural Health Monitoring of Long-span Bridges
1. REPORT NO. 1, 22 January 1998 TOP
State-of-the-Art in Vibration-Based Structural Damage Detection: Literature Review
CONTENTS
Chapter 1 Review of Vibration-Based Damage Detection Methods 1.1 Introduction 1.2 Methods Based on Measured Natural Frequencies 1.3 Methods Based on Measured Frequencies and Mode Shapes 1.4 Methods Based on Measured Frequency Response Functions 1.5 Methods Based on Measured Strain Modes 1.6 Other Methods References Chapter 2 Application of Damage Detection Methods in Bridge Structures 2.1 Introduction 2.2 Methods Based on Changes of Primary Modal Parameters 2.3 Other Advanced Methods 2.4 Comparison of Damage Detection Methods for Bridges 2.5 Application to Cable-Supported Bridges 2.6 Ambient Factors Affecting Modal Testing References Chapter 3 Related Work in Hong Kong Polytechnic University 3.1 Research on Damage Detection Methods 3.2 Research on Bridge Monitoring Techniques 3.3 Research on Weigh-in-Motion Methods References Chapter 4 Discussions and Conclusions 4.1 General Conclusions 4.2 Discussions and Suggestions for Further Work 4.3 Closing Remark References
Assessment Strategy of Possible Structural Damage in the Tsing Ma Bridge, Kap Shui Mun Bridge and Ting Kau Bridge
CONTENTS
Chapter 1 Introduction 1.1 Preface 1.2 Scope of the Report References Chapter 2 Assessment of Structural Damage in the Tsing Ma Bridge 2.1 Main Cables 2.2 Towers and Saddles 2.3 Cable Bands and Suspenders 2.4 Anchorages and Piers 2.5 Steel Deck Grillage 2.6 Supports and Bearings References Chapter 3 Assessment of Structural Damage in the Kap Shui Mun Bridge 3.1 Stay Cables and Attachments 3.2 Towers and Piers 3.3 Deck Grillage 3.4 Supports and Bearings References Chapter 4 Assessment of Structural Damage in the Ting Kau Bridge 4.1 Stay Cables and Attachments 4.2 Towers 4.3 Deck Grillage 4.4 Supports and Bearings References Chapter 5 Structural Modelling Methodology for Damage Detection 5.1 Concept of Damage-Detection-Orientated Modelling (DDOM) 5.2 Variational Principle for DDOM 5.3 Finite Element Implementation for DDOM 5.4 Summary References Chapter 6 Feasibility of Damage Detection Using Neural Networks .1 Overview 6.2 Back-Propagation (BP) Neural Network 6.3 Input Parameters and Pre-Processing 6.4 Influence of Modelling Errors 6.5 Influence of Measurement Errors 6.6 Summary References Chapter 7 Conclusions
Finite Element Modelling and Modal Sensitivity Analysis of the Tsing Ma Suspension Bridge CONTENTS
Chapter 1 Finite Element Modelling of the Tsing Ma Bridge 1.1 General Description 1.2 Classification of Computed Modes 1.3 Summary Chapter 2 Modal Sensitivity Analysis of the Tsing Ma Bridge 2.1 Simulated Damage Scenarios 2.2 Mode Correlation Check 2.3 Frequency Sensitivity 2.4 Mode Shape Sensitivity 2.5 Summary Chapter 3 Neural Network Based Hierarchical Identification Strategy 3.1 Concept of Hierarchical Identification 3.2 Damage Alarming Using Neural Network Filters 3.3 Hierarchical Identification of Damage Location and Extent 3.4 Summary References
Finite Element Modelling and Modal Sensitivity Analysis of the Kap Shui Mun Cable-Stayed Bridge
CONTENTS
Chapter 1 Finite Element Modelling of the Kap Shui Mun Bridge 1.1 General Description 1.2 Classification of Computed Modes 1.3 Summary Chapter 2 Modal Sensitivity Analysis of the Kap Shui Mun Bridge 2.1 Simulated Damage Scenarios 2.2 Mode Correlation Check 2.3 Frequency Sensitivity 2.4 Modal Shape Sensitivity 2.5 Summary
Finite Element Modelling and Modal Sensitivity Analysis of the Ting Kau Cable-Stayed Bridge
CONTENTS
Chapter 1 Finite Element Modelling of the Ting Kau Bridge 1.1 General Description 1.2 Classification of Computed Modes 1.3 Summary 19 Chapter 2 Modal Sensitivity Analysis of Simulated Scenarios for the Ting Kau Bridge 2.1 Simulated Scenarios 2.2 Mode Correlation Assurance 2.3 Frequency Sensitivity 2.4 Modal Shape Sensitivity 2.5 Summary
6. REPORT NO. 4(a), 26 December 1999 TOP
Damage Detection Simulation for the Tsing Ma Suspension Bridge
CONTENTS
Chapter 1 Damage Alarming Using Neural Network Filter 1.1 Simulated Damage Scenarios 1.2 Neural Network Based Novelty Index 1.3 Novelty Detection of Simulated Damage Scenarios 1.4 Summary References Chapter 2 Structural Damage Identification 2.1 Damage Type Identification and Regionalization Using Damage Index 2.2 Identification of Damaged Members Using ANN 2.3 Influence of Ambient Factors on Damage Identification 2.4 Summary
Damage Detection Simulation for the Kap Shui Mun Cable-Stayed Bridge
CONTENTS
Chapter 1 Damage Alarming Using Neural Network Filter 1.1 Simulated Damage Scenarios 1.2 Improved Novelty Index 1.3 Novelty Detection of Simulated Damage Scenarios 1.4 Summary References Chapter 2 Structural Damage Identification 2.1 Identification of Damage Location Using Damage Index 2.2 Influence of Ambient Factors on Damage Identification 2.3 Identification of Damaged Members Using ANN 2.4 Summary
Damage Detection Simulation for the Ting Kau Cable-Stayed Bridge
CONTENTS
Chapter 1 Damage Alarming Using Neural Network Filter 1.1 Simulated Damage Scenarios 1.2 Improved Novelty Index 1.3 Novelty Detection of Simulated Damage Scenarios 1.4 Summary References Chapter 2 Structural Damage Identification 2.1 Identification of Damage Location Using Damage Index 2.2 Influence of Ambient Factors on Damage Identification 2.3 Identification of Damaged Members Using ANN 2.4 Summary 9. REPORT NO. 5, 28 August 2000 TOP
Feasibility of Vibration-Based Damage Detection of the Tsing Ma Bridge, Kap Shui Mun Bridge and Ting Kau Bridge
CONTENTS
Chapter 1 Introduction 1.1 Overview of Tsing Ma, Kap Shui Mun and Ting Kau Bridges 1.2 Overview of Existing Sensory System 1.3 Feasibility of Vibration-based Damage Detection References and Figures Chapter 2 Feasibility of Detecting Damage Occurrence 2.1 Neural Network Based Novelty Detection Technique 2.2 Selection of Modal Parameters as Input Vector References and Figures Chapter 3 Feasibility of Detecting Damage Type and Location 3.1 Detection of Damage Region without Need of Structural Model 3.2 Detection of Damage Type and Location Based on Structural Model 3.3 Comparison of Modal Indices for Locating Damage References and Figures Chapter 4 Feasibility of Detecting Damaged Member and Extent 4.1 Back-propagation Neural Network 4.2 Damage Identification Based on Local Vibration Measurement References and Figures Chapter 5 Conclusions and Future Directions 5.1 Conclusions 5.2 Future Directions References and Figures
Appendix: List of Submitted Reports for Sub-Consultancy Agreement
327/PTeC |