An Investigation into the Application of Acceleration Responses' Trendline for Bridge Damage Detection Using...

Area of Science:

• Structural Engineering
• Civil Engineering
• Bridge Health Monitoring

Background:

• Structural damage detection is crucial for infrastructure safety.
• Previous methods utilized Savitzky-Golay and moving average filters for trendline analysis.
• Limitations exist in existing methods regarding noisy environments and baseline dependency.

Purpose of the Study:

• To develop and validate a novel trendline-based method for structural damage identification.
• To assess the effectiveness of quadratic regression in analyzing acceleration responses for damage detection.
• To evaluate the proposed method's performance under varying truck velocities and damage scenarios.

Main Methods:

• Employed quadratic regression to calculate trendlines from structural acceleration responses.
• Utilized normalized energies of trendlines as a damage index.
• Simulated structural damage as stiffness reduction in an ABAQUS model of a simply supported bridge.
• Tested the method with a truckload at velocities ranging from 1 m/s to 8 m/s.

Main Results:

• The proposed method successfully identified structural damage in noisy environments without dynamic modal parameter monitoring.
• Accuracy improved compared to previous trendline-based approaches.
• Damage was accurately detected in single- and multiple-damage scenarios at velocities up to 4 m/s.
• Some inaccuracies in damage location were observed at 8 m/s.

Conclusions:

• The quadratic regression-based trendline method offers a promising online, quick, and baseline-free approach for structural damage detection.
• The method demonstrates robustness in identifying damage under various conditions.
• Further research may be needed to optimize performance at higher velocities.