The adoption of wireless sensor networks has brought a significant breakthrough in structural health monitoring, providing an effective alternative to the challenges associated with traditional cable-based sensors. In recent years, a growing interest in developing contactless, visionbased vibration sensors like video cameras has led to advancements, potentially alleviating the previously mentioned drawbacks. In this study, a video of a vibrating frame is converted into a set of frames, so that local phase information can be extracted. The motion matrix is then derived from the phase information; since the number of measuring points is usually greater than the number of the excited modes of the system, the problem can become over-determined. Therefore, by applying dimensionality reduction techniques, the dimension of the motion matrix is significantly reduced. Finally, by exploiting an output-only identification technique, modal parameters are computed. The proposed approach is proven to accurately identify the structural frequencies and mode shapes.

Full-Field Modal Analysis Using Video Measurements and a Blind Source Separation Methodology

Mariani, Stefano
2023-01-01

Abstract

The adoption of wireless sensor networks has brought a significant breakthrough in structural health monitoring, providing an effective alternative to the challenges associated with traditional cable-based sensors. In recent years, a growing interest in developing contactless, visionbased vibration sensors like video cameras has led to advancements, potentially alleviating the previously mentioned drawbacks. In this study, a video of a vibrating frame is converted into a set of frames, so that local phase information can be extracted. The motion matrix is then derived from the phase information; since the number of measuring points is usually greater than the number of the excited modes of the system, the problem can become over-determined. Therefore, by applying dimensionality reduction techniques, the dimension of the motion matrix is significantly reduced. Finally, by exploiting an output-only identification technique, modal parameters are computed. The proposed approach is proven to accurately identify the structural frequencies and mode shapes.
2023
10th International Electronic Conference on Sensors and Applications
structural health monitoring; digital cameras; modal analysis; non-negative matrix factorization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1262099
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