Visual based laser speckle pattern recognition method for structural health monitoring

Kyeongtaek Park; Marco Torbol

doi:10.1117/12.2259851

12 April 2017 Visual based laser speckle pattern recognition method for structural health monitoring

Kyeongtaek Park, Marco Torbol

Proceedings Volume 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017; 101680L (2017) https://doi.org/10.1117/12.2259851
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2017, Portland, Oregon, United States

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.

Citation Download Citation

Kyeongtaek Park and Marco Torbol "Visual based laser speckle pattern recognition method for structural health monitoring", Proc. SPIE 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017, 101680L (12 April 2017); https://doi.org/10.1117/12.2259851

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KEYWORDS

Speckle

Cameras

Speckle pattern

Detection and tracking algorithms

Image processing

Structural health monitoring

Sensors

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