Accurate Correlation Modeling between Wind Speed and Bridge Girder Displacement Based on a Multi-Rate Fusion Method

Area of Science:

• Structural Engineering
• Environmental Monitoring
• Data Fusion Techniques

Background:

• Long-span bridges are susceptible to significant static and dynamic effects from wind action.
• Lateral wind speed is a primary driver of lateral displacement in bridge main girders.
• Accurate correlation modeling of wind speed and displacement is crucial for bridge safety and maintenance.

Purpose of the Study:

• To develop an improved multi-rate fusion method for correcting monitoring data.
• To achieve accurate correlation modeling between wind speed and bridge displacement.
• To enhance the reliability of data from Global Positioning System (GPS) and acceleration sensors.

Main Methods:

• Introduction of two Kalman gain coefficients to enhance the traditional multi-rate fusion method.
• Verification of the fusion method using simulated data analysis in both time and frequency domains.
• Application of the improved method to fuse lateral displacement and acceleration data from a bridge under strong wind action.

Main Results:

• The improved multi-rate fusion method effectively overcomes inaccuracies in high-frequency GPS and low-frequency acceleration sensor data.
• Fusion of monitoring data resulted in corrected lateral wind speed and displacement values.
• Established linear regression models showed an increased correlation coefficient and decreased confidence interval width for wind speed-displacement.

Conclusions:

• The improved multi-rate fusion method significantly enhances the accuracy of the wind speed-displacement correlation model.
• This data fusion technique offers a more reliable approach for analyzing bridge responses to wind action.
• The findings contribute to better structural health monitoring and risk assessment for long-span bridges.