Academic Journal

An Image-Based Framework for Measuring the Prestress Level in CFRP Laminates: Experimental Validation

التفاصيل البيبلوغرافية
العنوان: An Image-Based Framework for Measuring the Prestress Level in CFRP Laminates: Experimental Validation
المؤلفون: Jónatas Valença, Cláudia Ferreira, André G. Araújo, Eduardo Júlio
المصدر: Materials; Volume 16; Issue 5; Pages: 1813
بيانات النشر: Multidisciplinary Digital Publishing Institute
سنة النشر: 2023
المجموعة: MDPI Open Access Publishing
مصطلحات موضوعية: machine learning, deep learning, computer vision, CFRP laminates, strengthening RC, strain monitoring
الوصف: Image-based methods have been applied to support structural monitoring, product and material testing, and quality control. Lately, deep learning for compute vision is the trend, requiring large and labelled datasets for training and validation, which is often difficult to obtain. The use of synthetic datasets is often applying for data augmentation in different fields. An architecture based on computer vision was proposed to measure strain during prestressing in CFRP laminates. The contact-free architecture was fed by synthetic image datasets and benchmarked for machine learning and deep learning algorithms. The use of these data for monitoring real applications will contribute towards spreading the new monitoring approach, increasing the quality control of the material and application procedure, as well as structural safety. In this paper, the best architecture was validated during experimental tests, to evaluate the performance in real applications from pre-trained synthetic data. The results demonstrate that the architecture implemented enables estimating intermediate strain values, i.e., within the range of training dataset values, but it does not allow for estimating strain values outside those range. The architecture allowed for estimating the strain in real images with an error ∼0.5%, higher than that obtained with synthetic images. Finally, it was not possible to estimate the strain in real cases from the training performed with the synthetic dataset.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
Relation: Advanced Composites; https://dx.doi.org/10.3390/ma16051813
DOI: 10.3390/ma16051813
الاتاحة: https://doi.org/10.3390/ma16051813
Rights: https://creativecommons.org/licenses/by/4.0/
رقم الانضمام: edsbas.55134D32
قاعدة البيانات: BASE