基于惯性传感器的输电线路舞动信号处理技术

Here, to accurately identify characteristic parameters of transmission line galloping, a galloping signal processing algorithm based on 6-axis inertial sensor was proposed. Based on the theory of strapdown inertial navigation, a framework for calculating galloping signals was designed. A 3-DOF galloping model was used to do inversion and attitude calculation. By establishing inertial sensor acceleration and gyroscope error model, a non-directional fast calibration algorithm was used to do calibration and compensation for deterministic errors. Wavelet threshold denoising algorithm was used to denoise environmental white noise. The optimal wavelet basis functions and threshold choosing principle were determined. The initial quaternion was calculated by measuring pitch and roll angles with 2-direction unevenness to do attitude updating, and the algorithm to identify amplitude and frequency of galloping was realized. In lab environment, simple pendulum motion was used to simulate actual galloping signals. After signal processing, the identification of galloping characteristic parameters was better realized. The calculation results showed that the maximum galloping amplitude error is 3. 58%, and the maximum frequency error is 3. 67% .