Table of Contents
1 Cover
7 Preface
9 1 Introduction 1.1 Structural Health Monitoring: A Quick Review 1.2 Computer Vision Sensors for Structural Health Monitoring 1.3 Organization of the Book
10 2 Development of a Computer Vision Sensor for Structural Displacement Measurement 2.1 Vision Sensor System Hardware 2.2 Vision Sensor System Software: Template‐Matching Techniques 2.3 Coordinate Conversion and Scaling Factors 2.4 Representative Template Matching Algorithms 2.5 Summary
11 3 Performance Evaluation Through Laboratory and Field Tests 3.1 Seismic Shaking Table Test 3.2 Shaking Table Test of Frame Structure 1 3.3 Seismic Shaking Table Test of Frame Structure 2 3.4 Free Vibration Test of a Beam Structure 3.5 Field Test of a Pedestrian Bridge 3.6 Field Test of a Highway Bridge 3.7 Field Test of Two Railway Bridges 3.8 Remote Measurement of the Vincent Thomas Bridge 3.9 Remote Measurement of the Manhattan Bridge 3.10 Summary
12 4 Application in Modal Analysis, Model Updating, and Damage Detection 4.1 Experimental Modal Analysis 4.2 Model Updating as a Frequency‐Domain Optimization Problem 4.3 Damage Detection 4.4 Summary
13 5 Application in Model Updating of Railway Bridges under Trainloads 5.1 Field Measurement of Bridge Displacement under Trainloads 5.2 Formulation of the Finite Element Model 5.3 Sensitivity Analysis and Finite Element Model Updating 5.4 Dynamic Characteristics of Short‐Span Bridges under Trainloads 5.5 Summary
14 6 Application in Simultaneously Identifying Structural Parameters and Excitation Forces 6.1 Simultaneous Identification Using Vision‐Based Displacement Measurements 6.2 Numerical Example 6.3 Experimental Validation 6.4 Summary
15 7 Application in Estimating Cable Force 7.1 Vision Sensor for Estimating Cable Force 7.2 Implementation in the Hard Rock Stadium Renovation Project 7.3 Implementation in the Bronx‐Whitestone Bridge Suspender Replacement Project 7.4 Summary
16 8 Achievements, Challenges, and Opportunities 8.1 Capabilities of Vision‐Based Displacement Sensors: A Summary 8.2 Sources of Error in Vision‐Based Displacement Sensors 8.3 Vision‐Based Displacement Sensors for Structural Health Monitoring 8.4 Other Civil and Structural Engineering Applications 8.5 Future Research Directions
17 Appendix: Fundamentals of Digital Image Processing Using MATLAB A.1 Digital Image Representation A.2 Noise Removal A.3 Edge Detection A.4 Discrete Fourier Transform
18 References
19 Index
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