| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560400 |
| ISSN: | 1405-5546 |
| Autores: | Ayala Landeros, José Gabriel1 Castaño Meneses, Victor Manuel2 Becerra Rodríguez, María Blanca1 Servín Guzmán, Saulo1 Román Flores, Sonia Elizabeth1 Olivares Ramírez, Juan Manuel3 |
| Instituciones: | 1Instituto Tecnológico de San Juan del Río, San Juan del Río, Querétaro. México 2Universidad Nacional Autónoma de México, Juriquilla, Querétaro. México 3Universidad Tecnológica de San Juan del Río, San Juan del Río, Querétaro. México |
| Año: | 2018 |
| Periodo: | Oct-Dic |
| Volumen: | 22 |
| Número: | 4 |
| Paginación: | 1473-1485 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | A set of images of metal pieces with different finishes was obtained for use as a standard reference in the estimate of the surface roughness (Ra) through the fractal dimension (D) of the power spectrum and the spectrum of intensities. A system of artificial vision with two sources of LED light illumination (white and red) and three angles of incidence was used. The best results were found with the spectra of intensities regardless of the type of lighting or the angle of incidence. The values of the fractal dimension were correlated with the surface roughness values obtained with a contact profilometer to build regression curves that are used to estimate the surface roughness on site with a statistical error under 5%. This system could be used as an inspection station to reduce waiting times and unnecessary transport (Poka Yoke System). |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial |
| Keyword: | Fractal dimension, Wigner distribution, Power spectrum, Roughness, Poka Yoke, Artificial intelligence |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
