1. Project

Research and development project

🎙️Gutiérrez

System based on artificial vision cameras for the detection and evaluation of surface defects in metallic materials.

Research objectives

Non-destructive testing using artificial vision on metallic materials can be used in conjunction with other inspection techniques to reduce diagnostic errors. In this sense, deep learning as applied to artificial vision aims to create mathematical models that learn from images that contain cracks or other types of surface damage. The huge amounts of data that artificial neural networks must analyze require the use of highly efficient algorithms. The following objectives were established to respond to these proposals:

General objectives

✅ Create specific algorithms that run on dedicated hardware to detect and evaluate surface defects in metallic materials using the non-destructive testing technique through use of artificial vision.

Specific objectives

✅Establish image processing techniques and deep learning to apply non-destructive artificial vision research.

✅Expand the study of defectology, which the artificial vision method can provide as a necessary complement.

✅Establish the dataset for artificial neural network training.

✅Interpret the results of artificial neuronal network training to predict the defectology under study.

✅Develop programming and implementation skills in the appropriate programming language for the task.