Eventos Anais de eventos
COBEM 2023
27th International Congress of Mechanical Engineering
Computer vision and three dimensional profilometry applied to corrosion detection in deep rolled AISI 1045 steel.
Submission Author:
Vinicius Melo Cangussu , MG , Brazil
Co-Authors:
Gabriel Vieira, Vinicius Melo Cangussu, Alexandre Abrao
Presenter: Vinicius Melo Cangussu
doi://10.26678/ABCM.COBEM2023.COB2023-0617
Abstract
Metallic components are designed to operate under various environments, which may expose the materials to different adversities. Among these adversities is corrosion, which is an ordinary process that can decrease the lifespan and performance of components. Therefore, it is important to seek new approaches to identify and protect materials from corrosion in order to ensure the suitable functioning of these components and safety. This work proposes alternative ways to identify corrosion on the surface of materials and to investigate the influence of deep rolling on corrosion resistance. Therefore, the main goal of this research is to investigate the influence of deep rolling feed on the corrosion resistance of forged AISI 1045 steel (average hardness of 212 HV). The corrosion tests, which followed deep rolling, consisted of subjecting the samples in a 3,5% NaCl aqueous solution for 72 hours. A computer vision algorithm, based on the Python programming language, and three dimensional profilometry were employed to identify and evaluate the surface of the deep rolled samples. The results indicate that this algorithm is capable of identifying and counting, using optical microscopy images, the contours of points and small areas formed by localized corrosion. In conclusion, this research presents a promising approach to address the corrosion protection by proposing new techniques for identification and mitigation its effects. The implementation of a computer vision algorithm has demonstrated as a useful tool for identifying and evaluating surface corrosion, and the investigation of deep rolled parameter has provided valuable insights into the behavior of the surface integrity in contact with the corrosive attack. The potential impact of these findings spans across various engineering fields, such as aircraft construction, automotive industry, and the outcomes hold potential for developing new corrosion prevention and control strategies with significant implications for improving the safety and efficiency of metallic components.
Keywords
Deep rolling, algorithms, Corrosion analysis, Forged AISI 1045 steel
