Presentation + Paper
9 May 2024 Automated AI-DIC marker-less technique for tracking displacements of large structures
Author Affiliations +
Abstract
Markers are crucial for measuring the displacement of large structures using digital image correlation (DIC). In general, creating or affixing artificial markers on large structures is challenging. Several studies in the past have addressed this challenge by employing marker-less or target-free approaches. In this work, we integrate an AI-based non-intersecting poly-shape marker identification technique with the DIC program that uses the structural pattern as a marker and automates the selection of the region of interest by enabling strong correlation criteria to obtain the displacements in real-time. The proposed AI-DIC algorithm segments non-intersecting poly-shape markers from the images of the target structure based on the features detected by the KAZE feature detector and descriptors. Further, the investigated marker or the natural structural pattern is automatically given as an input region of interest to the DIC program. Moreover, it considers the marker as a template, correlates it with all subsequent images, and analyzes the displacements and frequencies of the target structure. In addition, the AI-DIC algorithm is realized on an in-house cantilever beam experiment where the images are acquired and processed in real-time.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sneha Prasad, Chih-Hung Chiang, David Kumar, Sumit Kalra, and Arpit Khandelwal "Automated AI-DIC marker-less technique for tracking displacements of large structures", Proc. SPIE 12950, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVIII, 129500J (9 May 2024); https://doi.org/10.1117/12.3012481
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KEYWORDS
Algorithm development

Digital image correlation

Detection and tracking algorithms

Wind turbine technology

Pipes

Image segmentation

Sensors

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