Spatio-Temporal Collaborative Optimization and Spatial Sensitivity Calibration for Portable Quartz Piezoelectric Weigh-in-Motion Sensors

Portable quartz piezoelectric Weigh-In-Motion (WIM) systems frequently suffer from low accuracy due to environmental noise and spatial sensitivity non-uniformity (SSNU), particularly under complex dynamic loading conditions. Previous studies often lack rigorous validation in realistic measurement scenarios. To address these challenges and ensure practical applicability, this paper proposes a multi-modal optimization method integrating novel sensor mechanics, hybrid filtering, and spatial compensation. First, a robust sensor structure featuring an oscillation damping layer and a pre-tightening stabilization mechanism was designed, optimizing the damping ratio to 0.2 – 0.3 to stabilize dynamic response. Second, a hybrid filtering architecture combining zero-phase high-pass filtering with custom chirp wavelet thresholding was developed. This method effectively extracts impact features from power frequency interference, improving the Signal-to-Noise Ratio (SNR) by 17.32 dB. Crucially, to validate the system under realistic weighing conditions, a comprehensive experimental campaign was conducted, including multi-point dynamic loading and variable impact tests. Based on the experimental data, a multiregion nonlinear position compensation model was established. Results demonstrate that this model achieves a coefficient of determination (R2) of 0.9918 in the central load-bearing zone and reduces the Spatial Sensitivity Non-Uniformity (SSNU) in this region by 72.56%, significantly lowering the coefficient of variation (CV) of the central zone to within 10%. Furthermore, statistical evaluation confirms significantly improved spatial sensitivity uniformity across different loading zones.This study provides a validated, high-precision solution for portable dynamic weighing in smart transportation infrastructure.