Vision-based monitoring receives increased attention for measuring displacements of civil infrastructure such as towers and bridges. Currently, most field applications rely on artificial targets for video processing convenience, leading to high installation effort and focus on only single-point displacement measurement e.g. at mid-span of a bridge. This study proposes a low-cost and non-contact vision-based system for multi-point displacement measurement based on a consumer-grade camera for video acquisition and a custom-developed package for video processing. The system has been validated on a cable-stayed footbridge for deck deformation and cable vibration measurement under pedestrian loading. The analysis results indicate that the system provides valuable information about bridge deformation of the order of a few cm induced, in this application, by pedestrian passing. The measured data enables accurate estimation of modal frequencies of either the bridge deck or the bridge cables and could be used to investigate variations of modal frequencies under varying pedestrian loads.

https://onlinelibrary.wiley.com/doi/epdf/10.1002/stc.2155

A non‐contact vision‐based system for multipoint displacement monitoring in a cable‐stayed footbridge

Investigation of dynamic properties of long‐span cable‐stayed bridges based on one‐year monitoring data under normal operating condition

Conventional damage detection techniques are gradually being replaced by state-of-the-art smart monitoring and decision-making solutions. Near real-time and online damage assessment in structural h...

https://journals.sagepub.com/doi/pdf/10.1177/14759217211036880

Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights:

Damage detection is one of the most important tasks for structural health monitoring of civil infrastructure. Before a damage detection algorithm can be applied, the integrity of the data must be e...

Toward data anomaly detection for automated structural health monitoring: Exploiting generative adversarial nets and autoencoders

Automated modal identification using principal component and cluster analysis: Application to a long-span cable-stayed bridge

The long-span bridge, characterized by slenderness and flexibility, is particularly sensitive to wind action. Extreme wind events, including typhoons and hurricanes, will threaten the safet...

Jian-Xiao Mao

Papers

Investigation of dynamic properties of long‐span cable‐stayed bridges based on one‐year monitoring data under normal operating condition

Toward data anomaly detection for automated structural health monitoring: Exploiting generative adversarial nets and autoencoders

Probabilistic Framework with Bayesian Optimization for Predicting Typhoon-Induced Dynamic Responses of a Long-Span Bridge

Modeling and forecasting of temperature-induced strain of a long-span bridge using an improved Bayesian dynamic linear model

A probabilistic approach for short-term prediction of wind gust speed using ensemble learning