Revista: | Computación y sistemas |
Base de datos: | |
Número de sistema: | 000560384 |
ISSN: | 1405-5546 |
Autores: | Campos Dominguez, Armando1 Ceballos Ceballos, Yessica I2 Zamora Castro, Sergio A3 Hernandez Martínez, Eliseo2 Velázquez Camilo, Oscar2 |
Instituciones: | 1Universidad Veracruzana, Facultad de Ingeniería Mecánica y Eléctrica, Xalapa, Veracruz. México 2Universidad Veracruzana, Facultad de Ciencias Químicas, Xalapa, Veracruz. México 3Universidad Veracruzana, Facultad de Ingeniería de la Construcción y el Hábitat, Xalapa, Veracruz. México |
Año: | 2018 |
Periodo: | Oct-Dic |
Volumen: | 22 |
Número: | 4 |
Paginación: | 1147-1155 |
País: | México |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Resumen en inglés | Due to the increasing demands of quality products, efficient monitoring systems in the current control and operation of industrial processes are essentials. However, in particulate processes as cane sugar crystallization, accurate, inexpensive and suitable sensors for the online monitoring of key process variables are not available. In this work, an alternative using the image analysis of micrographs captured in batch cooling crystallizer is presented. The propose is based on a combined treatment between fractal analysis and conventional binarization techniques, obtaining a normalized fractal index (NFI) that allow the dynamic monitoring of crystal mean diameter, D(4,3). In order to evaluate the monitoring system, the crystallizer was operated at different cooling profiles, finding that the methodology proposed can be used as an alternative technique, inexpensive and easy to implement, for monitoring crystal growth. |
Disciplinas: | Ciencias de la computación |
Palabras clave: | Procesamiento de datos |
Keyword: | Cane sugar crystallization, Monitoring crystal growth, Image fractal analysis, Data processing |
Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |