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Fault detection for recycled rubber and glass material implementation via digital image processing

    Arigela Surendranath Ramana P.V.

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue 6S, Pages 102-110
10.47392/irjash.2021.174

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Abstract

The study exhibits to understand the cracks generation and propagation inside the material as a source of the identification. The research is based primarily on the assessment of deflection, tension, and fracture propagation in structures through digital image processing (DIP) and its correlation. The DIP is a non-destructive assessment technique to capture microstructure pictures and loading in various loading scenarios. In order to monitor features and assign their position to a defined coordinate system, photogrammetry concepts are applied. The generated displacement data represents the typical movement present concerning the initial location in the centre of the tiny sub-images employed in the analysis. Aerial or satellite photos collected before and after the earthquake may currently be analyzed in techniques to deduce co-seismic terrain malformations with sub-pixel correlation. Due to the intrinsic diversity of natural faults and deformations, the interpretation of this data is not straightforward. The study of the correlation with either program clearly shows the relative shifts, the friction interface, the rupture arrest on the border, and wing fractures. The observations of displacement collected are transformed into strains using non-local denoising algorithms. This work is the first step in combining the digital picture association approach with high-speed photography to record transient dynamic rupture events. For measuring surface movement and tension in concrete, the DIP technology and the MATLAB® Program tracking have been employed.
Keywords:
    Structural health monitoring, Fault detection, Crack propagation Digital image process, Frictional interface, Damage assessment
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(2021). Fault detection for recycled rubber and glass material implementation via digital image processing. International Research Journal on Advanced Science Hub, 3(Special Issue 6S), 102-110. doi: 10.47392/irjash.2021.174
Arigela Surendranath; Ramana P.V.. "Fault detection for recycled rubber and glass material implementation via digital image processing". International Research Journal on Advanced Science Hub, 3, Special Issue 6S, 2021, 102-110. doi: 10.47392/irjash.2021.174
(2021). 'Fault detection for recycled rubber and glass material implementation via digital image processing', International Research Journal on Advanced Science Hub, 3(Special Issue 6S), pp. 102-110. doi: 10.47392/irjash.2021.174
Fault detection for recycled rubber and glass material implementation via digital image processing. International Research Journal on Advanced Science Hub, 2021; 3(Special Issue 6S): 102-110. doi: 10.47392/irjash.2021.174
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