High-Resolution Performance Assessment of Bridges: An Indirect Modal Identification Framework Using Vehicle–Bridge Contact-Point Response

Abstract

Structural health monitoring (SHM) plays a critical role in assessing the operational safety and preventing potential failures of bridge infrastructure. However, traditional direct measurement methods requiring dense sensor arrays are often constrained by high instrumentation costs and low spatial resolution, limiting their efficacy for detailed performance assessment. To address these deficiencies, this study proposes a novel indirect modal identification framework that integrates the vehicle-bridge contact-point response with local mean decomposition (LMD) and functions as a continuous mobile scanner. Distinct from conventional approaches, this method exploits the physical characteristic that the contact-point response envelope intrinsically maps to the bridge’s spatial vibration profile, thereby eliminating the masking effect of vehicle frequencies and avoiding boundary-effect distortions common to Hilbert transform-based techniques. Recognizing the inherent complexities and high costs of field testing in indirect monitoring, this study presents a comprehensive numerical validation as an essential preliminary stage. The proposed framework achieves high-precision extraction of the first three bridge mode shapes, maintaining modal assurance criterion (MAC) values not lower than 0.9998 under smooth road conditions. Notably, the method exhibits strong robustness in simulated operational environments, remaining effective under significant environmental noise ( SNR = 20    dB ) and random traffic interference. Although road surface roughness presents a challenge for higher-order modes, the method remains effective for fundamental mode identification. By providing a cost-effective, high-resolution solution that obviates the need for bridge-mounted sensors, this research contributes a robust technical framework for rapid condition assessment and decision-making in bridge maintenance.