Modal identification of building structures using vision-based measurements from multiple interior surveillance cameras

Surveillance cameras are ubiquitous within modern building systems, providing a wealth of data that, to date, has not been utilized for structural health monitoring and condition assessment. In this paper, a vision-based vibration-monitoring technique is introduced, which leverages existing cameras within building structures to extract modal information and assess for damage. Cameras already installed within buildings, such as interior surveillance cameras, are used to measure structural responses (inter-story drifts and rotations) by tracking the cameras' motion relative to the floor below. By synchronizing vision-based inter-story measurements captured at multiple stories, a complete three-dimensional representation of the building's motion is recovered. Output-only system identification (frequency domain decomposition) is applied to these vision-based measurements to extract modal information-frequencies and mode shapes. An experimental parametric study on a lab-scale three-story structure is conducted to assess the efficacy of the vision-based monitoring technique for structural modal identification. The primary set of structure/camera geometries considered is representative of actual surveillance camera installations. Broadband white noise is used to excite the structure uni- and bidirectionally, and the resulting ambient and transient responses are measured. The accuracy of the modal information extracted by means of the proposed vision-based technique is assessed through comparison with modal data from accelerometer-based measurements, quantified by the modal assurance criteria. Moreover, the precision, robustness, and repeatability of the method as well as its shortcomings are established and are described in this paper.

Automated summary

This paper introduces a vision-based vibration-monitoring technique that utilizes existing cameras within building structures to extract modal information and assess for damage. The technique tracks cameras' motion to measure structural responses and uses system identification to extract modal information. An experimental study on a lab-scale structure is conducted to assess the effectiveness of the technique.