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Data Matching Methods for FBG Dynamic Strain Signal

FBG strain sensors are often used for strain monitoring inside bridge structures and its sensitivity coefficient directly affects the measurement results, so its sensitivity coefficient must be calibrated before use. Due to the inconsistency of the sensor sampling frequency and time-delay characteristics, the measured value sequences of the sensor to be calibrated and the reference sensor often have time misalignment, which will have a great impact on the calibration results of the sensitivity coefficient of the FBG sensor. In this paper, classical cross-correlation, wavelet cross-correlation and dynamic time warping algorithm are used to perform data matching. By using a cantilever beam to simulate a bridge structure, the data matching of dynamic strain data of FBG sensor and resistance strain gauge is carried out. The experimental results show that the dynamic time warping algorithm effectively solves the problem of time dislocation of sensor data, and the data matching effect is the best.