A COMPUTER VISION SYSTEM FOR PREDICTING DAMAGE TO STRUCTURAL MATERIALS – MSc. Bakhtiyar Mammadli

Project title:

AI-Driven Computer Vision Framework for Early Failure Prediction and Identification of Failure-Prone Zones in Structural Materials

 

Abstract:

The project aims to develop an AI-based approach for early assessment of deformation and failure processes in structural materials. By combining advanced image-based measurements with machine learning, the project will investigate how the evolution of deformation patterns can be used to identify critical material states and failure-prone regions before macroscopic failure occurs. Experimental tensile testing and Digital Image Correlation (DIC) will be used to generate full-field deformation data for the development and validation of the proposed methods. The developed approaches will be integrated into a prototype software solution for automated analysis and visualization of material behaviour. The project is intended to provide a foundation for further industrial adaptation in areas such as material testing, structural integrity assessment, quality control, and advanced monitoring systems.

 

Funding body: Science4Business – Inkubator Rozwoju S4B

Duration: 18 months

Budget: 100,000 PLN



This project has received funding from the European Union Horizon 2020 research and innovation
programme under grant agreement No 857470 and from European Regional Development Fund
via Foundation for Polish Science International Research Agenda PLUS programme grant
No MAB PLUS/2018/8.
Poland
The project is co-financed from the state budget within the framework of the undertaking of the Minister of Science and Higher Education "Support for the activities of Centers of Excellence established under Horizon 2020".

Grant: 5 143 237,70 EUR
Total value: 29 971 365,00 EUR
Date of signing the funding agreement: December 2023

The purpose of the undertaking is to support entities of the higher education and science system that have received funding from the European Union budget in the competition H2020-WIDESPREAD-2018-2020/WIDESPREAD-01-2018-2019: Teaming Phase 2. in the preparation, implementation and updating of activities, maintenance of material resources necessary for carrying out activities, acquisition and modernization of scientific and research apparatus, maintenance and development of personnel potential necessary for the implementation of activities, and dissemination of the results of scientific activities.