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Proceedings Paper

Visual based laser speckle pattern recognition method for structural health monitoring
Author(s): Kyeongtaek Park; Marco Torbol
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Paper Abstract

This study performed the system identification of a target structure by analyzing the laser speckle pattern taken by a camera. The laser speckle pattern is generated by the diffuse reflection of the laser beam on a rough surface of the target structure. The camera, equipped with a red filter, records the scattered speckle particles of the laser light in real time and the raw speckle image of the pixel data is fed to the graphic processing unit (GPU) in the system. The algorithm for laser speckle contrast analysis (LASCA) computes: the laser speckle contrast images and the laser speckle flow images. The k-mean clustering algorithm is used to classify the pixels in each frame and the clusters’ centroids, which function as virtual sensors, track the displacement between different frames in time domain. The fast Fourier transform (FFT) and the frequency domain decomposition (FDD) compute the modal properties of the structure: natural frequencies and damping ratios. This study takes advantage of the large scale computational capability of GPU. The algorithm is written in Compute Unifies Device Architecture (CUDA C) that allows the processing of speckle images in real time.

Paper Details

Date Published: 12 April 2017
PDF: 7 pages
Proc. SPIE 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017, 101680L (12 April 2017); doi: 10.1117/12.2259851
Show Author Affiliations
Kyeongtaek Park, Ulsan National Institute of Science and Technology (Korea, Republic of)
Marco Torbol, Ulsan National Institute of Science and Technology (Korea, Republic of)


Published in SPIE Proceedings Vol. 10168:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017
Jerome P. Lynch, Editor(s)

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