Year: 2026
Type: article
Abstract: Structural vibrations can provide valuable insights from their fundamental dynamic characteristics, and detected changes in modal parameters can be an indicator of modifications in the structure’s physical properties, possibly caused by damage or deterioration. Structural Health Monitoring is therefore crucial for early damage detection and assessment. Vibration analysis is mainly performed using physically installed sensors, a mature and reliable technology that offers high-precision data and an optimal signal-to-noise ratio but requires physical mounting, often in difficult access areas and, over time, maintenance and sensor calibration directly onto the structure, with time-consuming, costly, and potentially disruptive processes. In contrast, non-contact techniques work without physical installations, can monitor wide areas or multiple points simultaneously, and are often easier to set up or adapt to different structures, although with limitations in precision, temporal resolution, sensitivity under low light conditions, and/or data throughput. This work introduces a vision-based framework for non-contact modal analysis using neuromorphic cameras, a novel class of visual sensors that asynchronously record pixel-level brightness changes. The proposed method is validated in both controlled laboratory experiments on a cantilever beam and on a real-scale bridge specimen subjected to traffic-induced vibrations. The results demonstrate the feasibility and effectiveness of neuromorphic camera-based vibration monitoring for structural health assessment in real-world scenarios.
Source: Procedia Structural Integrity
Authors: Dario Cazzato, Giovanni Vaglica, Flavio Bono
Institutions: European Commission, Joint Research Centre, Fincons Group (Italy)
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7214714513