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A Bio-Inspired Frequency-Based Approach for Tailorable and Scalable Speckle Pattern Generation

التفاصيل البيبلوغرافية
العنوان: A Bio-Inspired Frequency-Based Approach for Tailorable and Scalable Speckle Pattern Generation
المؤلفون: Ivan Bartoli, Matthew McCarthy, Shakerur Ridwan, Antonios Kontsos, Brian Wisner, Melvin Mathew
المصدر: Experimental Mechanics. 60:1103-1117
بيانات النشر: Springer Science and Business Media LLC, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Digital image correlation, Mean squared error, business.industry, Computer science, Mechanical Engineering, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Point cloud, Aerospace Engineering, Pattern recognition, Context (language use), 02 engineering and technology, 021001 nanoscience & nanotechnology, Reduction (complexity), Speckle pattern, 020303 mechanical engineering & transports, 0203 mechanical engineering, Mechanics of Materials, Region of interest, Scalability, Artificial intelligence, 0210 nano-technology, business
الوصف: Digital Image Correlation (DIC) is a length scale independent surface pattern matching and tracking algorithm capable of providing full field deformation measurements. The confident registration of this pattern within the imaging system becomes key to the derived results. Practically, conventional speckling methods use non-reliable, non-repeatable patterning methodologies including spray paints and air brushing leading to increased systematic and random errors based on the user’s experience. A methodology to develop a speckle pattern tailored to the imaging and experimental conditions of the given system is developed in this paper. In this context, a novel bio-inspired speckle pattern development technique is introduced, leveraging spatial imaging parameters in addition to frequency characteristics of speckle patterns, enhancing the results obtained through DIC. This novel technique leverages gradient parameters in the frequency spectrum obtained from patterns fabricated using a bio-templating manufacturing technique. The analysis presented shows that optimized gradient features alongside tailored spatial characteristics reduce errors while increasing the usefulness of DIC results across the entire region of interest. With this new approach, gradient information is derived from the bio-templated pattern, extracted, optimized and then convolved with spatial properties of a numerically generated 2D point clouds which can then be transferred onto actual specimens. Numerical error analysis shows that the optimized patterns result in significant reduction in root mean square error compared to conventional speckling methods. Physical experiments show the scalability of this optimized pattern to allow for varying working distances while consistently maintaining a lower error threshold compared to conventional speckling techniques.
تدمد: 1741-2765
0014-4851
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::9978745f73d264a2d3547551398b9aa6
https://doi.org/10.1007/s11340-020-00631-3
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........9978745f73d264a2d3547551398b9aa6
قاعدة البيانات: OpenAIRE
الوصف
تدمد:17412765
00144851