This book presents extensive information on structural health monitoring for suspension bridges. During the past two decades, there have been significant advances in the sensing technologies employed in long-span bridge health monitoring. However, interpretation of the massive monitoring data is still lagging behind. This book establishes a series of measurement interpretation frameworks that focus on bridge site environmental conditions, and global and local responses of suspension bridges. Using the proposed frameworks, it subsequently offers new insights into the structural behaviors of long-span suspension bridges. As a valuable resource for researchers, scientists and engineers in the field of bridge structural health monitoring, it provides essential information, methods, and practical algorithms that can facilitate in-service bridge performance assessments.

Part 1
1 Temperature Action Monitoring of Main Girder
1.1 Introduction
1.2 The NSB Description and Instrumentation
1.3 Spatial and Temporal Characteristics of Temperature Measurements
1.4 Effective Temperature Analysis
1.4.1 Correlation of Ambient Air Temperature and Effective Temperature
1.4.2 Cycling Variation of Effective Temperature
1.5 Temperature Gradient Analysis
1.5.1 Transverse Temperature Differences
1.5.2 Vertical Temperature Differences
1.5.3 Correlation Analysis of Temperature Differences
1.6 Characteristic Values of Effective Temperature
and Temperature Gradients
1.7 Discussion of Temperature Actions for Potential Bridge Design Improvements
1.7.1 Effective Temperature
1.7.2 Temperature Gradients
1.8 Summary
References
2 Bridge-Site Extreme Wind Prediction
2.1 Introduction
2.2 The RSB Description and Wind Monitoring Instrumentation
2.3 Statistical Analysis of Wind Measurements
2.4 Maximum Entropy-Based Prediction Method
2.4.1 Basic Theory
2.4.2 Numerical Example
2.5 Prediction of Extreme Wind Velocity
2.5.1 Joint Probability Density Functions
2.5.2 Estimation of Model Parameters
2.5.3 Extreme Wind Velocities
2.6 Summary
Appendix
References
Part 2
3 Measurement-Based Damage Detection for Expansion Joints
3.1 Introduction
3.2 Displacement Monitoring of the RSB
3.3 Determination of Dominant Environmental Factors
3.4 Damage Detection of Expansion Joints
3.4.1 Correlation Models Between Displacements and Dominant Environmental Factors
3.4.2 Definition of Damage Detection Index
3.4.3 Statistical Control Chart
3.4.4 False Positive Tests
3.4.5 Damage Sensitivity Test
3.5 Summary
References
4 Modal Frequency-Based Structural Damage Detection
4.1 Introduction
4.2 Identification of Modal Frequencies for the RSB
4.3 Temperature-Induced Variability of Modal Frequencies
4.3.1 Correlation Analysis of Temperature-Frequency
4.3.2 Removal of Temperature Effect
4.4 Wind-induced and Traffic-Induced Modal Variability
4.4.1 Correlation Analysis of Traffic-Frequency
4.4.2 Correlation Analysis of Wind-Frequency
4.5 Framework of Damage Detection
4.5.1 Machine Learning-Based Frequency-Temperature Model
4.5.2 Probabilistically Modeling and Normalization
4.5.3 Control Charts of the Healthy Phase
4.5.4 Control Charts of the Unknown Phase
4.6 Framework Application
4.6.1 Elimination of the Temperature Effects
4.6.2 Normalization of the Modal Frequencies
4.6.3 Damage Detection Based on Control Chart
4.7 Summary
References
Part 3
5 Fatigue Monitoring of Welded Details
5.1 Introduction
5.2 Fatigue Stress Monitoring of the Runyang Yangtze Bridge
5.3 Fatigue Damage Determination Framework
5.3.1 S-N Curves of Welded Orthotropic Decks
5.3.2 Equivalent Stress Range and Fatigue Damage
5.4 Processing of Strain Measurements
5.4.1 Original Strain Data Analysis
5.4.2 Temperature Effect on Stress Range Histogram
5.4.3 Random Interference in Stress Range Histogram
5.5 Necessity of Long-Term Monitoring
5.5.1 Medium-Term Monitoring
5.5.2 Long-Term Monitoring
5.6 Fatigue Life Prediction
5.7 Summary
References
6 Fatigue Reliability Analysis for Welded Details
6.1 Introduction
6.2 Framework of the Fatigue Reliability Analysis
6.2.1 Fatigue Limit State Function
6.2.2 Probabilistic Model for the Equivalent Stress Range
6.2.3 Fatigue Reliability Estimation Methods
6.3 Fatigue Reliability of the Welded Details of the RSB
6.3.1 Stress Range Histograms
6.3.2 Probability Density Fun