This study presents an innovative approach to processing vibration signals in bridge structures, focusing on enhancing the accuracy of dynamic response measurements and structural health assessment. The research addresses the critical challenges in signal processing, particularly the uncertainties in determining filtering parameters for isolating dynamic components from static displacements.
A novel method for adaptive filter parameter selection is proposed, taking into account the variability of resonant frequencies and the non-linearity of quasi-static displacements due to moving loads. This approach significantly reduces errors in determining forced and natural vibration parameters, leading to more accurate assessments of the bridge's mechanical characteristics.
The study introduces an optimized algorithm for processing acceleration and velocity signals, improving the resolution in identifying natural frequencies of the structures. This method combines traditional Fast Fourier Transform (FFT) techniques with an innovative approach to spectral analysis, enabling more precise identification of resonant frequencies and damping coefficients.
A comprehensive evaluation framework is developed, integrating the analysis of vibration amplitudes, frequencies, and damping ratios. This framework provides a more robust assessment of the bridge's structural health, enhancing the ability to detect and characterize potential defects or changes in load-bearing capacity.
The practical value of this research lies in its application to real-world bridge diagnostics. Guidelines for sensor selection and configuration are provided, tailored to different bridge types and sizes. The proposed methods demonstrate significant improvements in the accuracy of dynamic coefficient determination and overall structural assessment, potentially reducing maintenance costs and enhancing safety.