Advanced Methods for Real-Time Signal Processing in Urban Bridge Inspections Using Wireless Sensors

This study introduces a method for processing various types of random real-world signals from bridges in both experimental models and real-world scenarios using a wireless sensor system. By analyzing and processing signals collected during actual traffic on bridges, the study identifies and provides parameters that meet current quality inspection requirements to ensure the safety of bridge users. The parameters investigated in this study include deformation, natural frequency, amplitude, impact factor, and damping coefficient. Research has determined and highlighted key parameters for assessing the quality of bridge spans to meet quality inspection standards. Using actual traffic vibration signals provides accurate and useful information that supports the government in conducting regular inspections. Furthermore, this study reduces inspection costs for regulatory agencies by significantly cutting costs compared to traditional methods, offering economic benefits. In general, this research not only introduces a new approach to vibration signal processing but also brings practical benefits to bridge infrastructure management and inspection.