Work

An innovative drive-through approach for structural testing and experimental insights from two cable stayed bridges

Year: 2025

Type: article

Abstract: Effective monitoring of bridge infrastructure is essential for ensuring safety, reliability, and longevity. Traditional Structural Health Monitoring (SHM) methods have been challenged by installation complexity, maintenance demands, and high costs, particularly in large-scale or long-span bridges. In response, a novel, non-intrusive drive-through method for extracting bridge eigenfrequencies has been developed using vehicle-multi-mounted Micro-Electro-Mechanical Systems (MEMS) sensors. A passing vehicle is thereby converted into a mobile sensing platform, and bridge dynamic properties are captured under normal traffic conditions. Experimental validation was conducted on Shanghai's Yangpu and Nanpu cable-stayed bridges, and eigenfrequency extraction from a single crossing was demonstrated, significantly reducing the need for multiple passes. The signal-to-noise ratio was improved by the fusion of data from multiple sensors, and frequency identification was achieved. A practical and cost-effective solution for large-scale bridge monitoring is thus offered, and further work is planned to extend the methodology to additional structural parameters and enhanced robustness. • Introduces a novel multisensor drive-through system for bridge monitoring that reduces repeated vehicle passes from up to 20 times to just a single crossing. • Employs LARA, a wireless MEMS accelerometer with Raspberry Pi-based data acquisition, enabling easy integration into modern electronic vehicles. • Accurately extracts bridge eigenfrequencies in one pass, significantly enhancing monitoring efficiency compared to traditional methods. • Successfully validated on Shanghai's Yangpu Bridge and Nanpu Bridge under normal traffic conditions. • Offers a cost-effective and non-intrusive solution that streamlines structural health monitoring for large-scale bridges.

Source: Developments in the Built Environment

DOI: 10.1016/j.dibe.2025.100653

Authors: Seyedmilad Komarizadehasl, Zhouhui Shen, Ye Xia, Mingming Song, Jose Turmo

Institutions: Universitat Politècnica de Catalunya, Tongji University, Shanghai Qi Zhi Institute

Language: English

Topic: Structural Health Monitoring Techniques

Subfield: Civil and Structural Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $3,230