2 resultados para 3D shape detection

em Digital Commons - Michigan Tech


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Mineral dust shape and roughness are important for a multitude of processes; it is known for aspherical shape but the true measurements in three dimensions are rare. Atomic Force Microscope was used for determine both 3D shape and roughness for two dust which are commonly used in laboratory experiments – Arizona Test Dust (ATD) and Kaolinite. We determined both of them are rather flat and round; an oblate spheroid would be a good model. Loess Filter was used to smooth the particles' surface and correlation analysis was used to examine the surfaces' properties of the dust; we found no features under 100nm scales. Also, our particles' surface area result is very similar to BET surface area.

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The bridge inspection industry has yet to utilize a rapidly growing technology that shows promise to help improve the inspection process. This thesis investigates the abilities that 3D photogrammetry is capable of providing to the bridge inspector for a number of deterioration mechanisms. The technology can provide information about the surface condition of some bridge components, primarily focusing on the surface defects of a concrete bridge which include cracking, spalling and scaling. Testing was completed using a Canon EOS 7D camera which then processed photos using AgiSoft PhotoScan to align the photos and develop models. Further processing of the models was done using ArcMap in the ArcGIS 10 program to view the digital elevation models of the concrete surface. Several experiments were completed to determine the ability of the technique for the detection of the different defects. The cracks that were able to be resolved in this study were a 1/8 inch crack at a distance of two feet above the surface. 3D photogrammetry was able to be detect a depression of 1 inch wide with 3/16 inch depth which would be sufficient to measure any scaling or spalling that would be required be the inspector. The percentage scaled or spalled was also able to be calculated from the digital elevation models in ArcMap. Different camera factors including the distance from the defects, number of photos and angle, were also investigated to see how each factor affected the capabilities. 3D photogrammetry showed great promise in the detection of scaling or spalling of the concrete bridge surface.