Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition

Area of Science:

• Structural Engineering
• Vibration Analysis
• Signal Processing

Background:

• Micro-electro-mechanical system (MEMS) accelerometers lack precision in converting vibration signals to elevation data.
• Accurate dynamic displacement monitoring is crucial for bridge structural health assessment.

Purpose of the Study:

• To propose a robust method for reconstructing bridge dynamic displacement from MEMS accelerometer data.
• To enhance the precision of elevation signal transformation by addressing integration challenges.

Main Methods:

• Ensemble Empirical Mode Decomposition (EEMD) to decompose vibration signals.
• Time domain integration combined with EEMD for displacement reconstruction.
• Simulation and experimental validation using bridge analog signals and a vibration test bench.

Main Results:

• The proposed EEMD and time domain integration method effectively eliminates low-frequency integral drift and high-frequency noise.
• The algorithm demonstrated superior adaptability and robustness compared to traditional methods.
• Field experiments on highway elevated bridges confirmed the method's effectiveness.

Conclusions:

• The developed method significantly improves the accuracy of dynamic displacement reconstruction for bridges.
• This approach offers a more reliable solution for structural health monitoring of bridges using MEMS accelerometers.