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Resumen

 

PROPOSAL OF A NEW KERNAL METHOD LAWS-BASED FOR SURFACE ROUGHNESS EVALUATION

PROPUESTA DE UN NUEVO KERNAL BASADO EN LAWS PARA EVALUAR LA RUGOSIDAD DE PIEZAS METALICAS
PhD. Sir Alexci Suarez.
PhD(c). Maribel González Rodríguez.
PhD. Albert Miyer Suárez.

Abstract: A new descriptor based in Laws is proposed in this paper that allows classifying turned metallic parts as function of their superficial roughness. The material used for the tests was the AISI 6150 steel, considered one of the reference steels in the market. The proposed solution is based on a vision system which calculates the actual roughness using as fundament the analysis of texture on the part images. The kernel developed to quantify the roughness is based on the R5R5 mask presented by Laws. The results of combining the proposed R5SR5S kernel with the standard diversion allows to classify the images with a rate of success of 95,87% using Linear Discriminant Analysis, and 97,3% using Quadratic Discriminant Analysis. These results demonstrate that the proposed technique can be effectively used to evaluate the roughness in machining processes.

Keywords: Roughness, Laws, co-occurrence matrix, surface texture.

Resumen: En este artículo se propone un nuevo descriptor basado en Laws, que permite clasificar piezas metálicas que han sido mecanizadas mediante operaciones de torneado evaluando la rugosidad superficial. La solución se basa en un sistema de visión el cual analiza la rugosidad presente en las imágenes a partir de la textura. Se han realizado operaciones de torneado utilizando la aleación AISI 6150. El kernel desarrollado para cuantificar la rugosidad se basa en el R5R5 presentado por Laws. Los resultados del kernel propuesto combinado con la desviación estándar permite clasificar las imágenes con una tasa de acierto de 95.87% con LDA y 97.3% con QDA, demostrando que puede ser utilizado para evaluar la rugosidad en procesos de mecanizado.

Palabras clave: Rugosidad, Laws, Matriz de co-ocurrencia, textura superficial.