研究目的
To investigate the dynamic and quasi-static signal separation method for long-gauge strain sensors under different vehicle loads and to study the dynamic monitoring performance of the long-gauge sensor for bridge health monitoring.
研究成果
The proposed method effectively separates dynamic and quasi-static strains from long-gauge FBG sensor data, with quasi-static strains accounting for a significant portion of the total strain. The method is robust against variations in vehicle speed and provides a reliable means for monitoring bridge stress states, supporting structural health monitoring applications.
研究不足
The study is limited to a specific bridge (Wanlongshan Bridge) and may not generalize to all bridge types. The method relies on accurate determination of the first-order natural frequency, which could be affected by environmental factors. The sensors are externally affixed, which might not capture internal structural changes effectively.
1：Experimental Design and Method Selection:
The study employs the empirical mode decomposition (EMD) method for signal separation, based on its advantages in handling nonstationary and nonlinear data. The method involves decomposing dynamic strain signals into intrinsic mode functions (IMFs) and residues to extract quasi-static components using the first-order natural frequency of the bridge as a threshold.
2：Sample Selection and Data Sources:
Data were collected from the Wanlongshan Bridge in Pingxiang City, Jiangxi Province, using long-gauge fiber Bragg grating (FBG) sensors installed on the bridge. The sensors included eight strain sensors and one temperature compensation sensor.
3：List of Experimental Equipment and Materials:
Long-gauge FBG sensors (gauge length 1 m, packaged with basalt fiber-reinforced polymer), calibration table for sensor calibration, dumper (32 tons) for dynamic load tests, and ANSYS software for modal analysis.
4：Experimental Procedures and Operational Workflow:
Sensors were installed on the bridge by cleaning the surface, fixing ends with structural adhesive, and securing with tin foil. Dynamic load tests were conducted with the dumper driving at speeds of 10, 20, and 30 km/h. Strain data were recorded and processed using EMD to separate dynamic and quasi-static components.
5：Data Analysis Methods:
Data analysis involved EMD for signal decomposition, Fast Fourier Transform (FFT) for frequency analysis, and comparison with modal analysis results from ANSYS to validate the separation method.
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