Implementación de una red neuronal para la detección de anomalías en bandejas

  1. Sánchez Santalices, Julián 1
  2. Moya de la Torre, Eduardo Julio 1
  3. Poncela Méndez, Alfonso Valentín 1
  1. 1 Universidad de Valladolid
    info

    Universidad de Valladolid

    Valladolid, España

    ROR https://ror.org/01fvbaw18

Livre:
XLIV Jornadas de Automática: libro de actas: Universidad de Zaragoza, Escuela de Ingeniería y Arquitectura, 6, 7 y 8 de septiembre de 2023, Zaragoza
  1. Ramón Costa Castelló (coord.)
  2. Manuel Gil Ortega (coord.)
  3. Óscar Reinoso García (coord.)
  4. Luis Enrique Montano Gella (coord.)
  5. Carlos Vilas Fernández (coord.)
  6. Elisabet Estévez Estévez (coord.)
  7. Eduardo Rocón de Lima (coord.)
  8. David Muñoz de la Peña Sequedo (coord.)
  9. José Manuel Andújar Márquez (coord.)
  10. Luis Payá Castelló (coord.)
  11. Alejandro Mosteo Chagoyen (coord.)
  12. Raúl Marín Prades (coord.)
  13. Vanesa Loureiro-Vázquez (coord.)
  14. Pedro Jesús Cabrera Santana (coord.)

Éditorial: Servizo de Publicacións ; Universidade da Coruña

ISBN: 9788497498609

Année de publication: 2023

Pages: 873-878

Congreso: Jornadas de Automática (44. 2023. Zaragoza)

Type: Communication dans un congrès

Résumé

The aim of this paper is the detection of several types of defects which appear at the biodegradable trays during its fabrication, specifically at the input and output of the laminate process. For that, it is used an artificial vision system that: analyzes the trays through the production line, selects the defectives and ejects them if neccesary. This artificial vision system is has: three cameras, two of them located at the input of the process and the other one at the output; a PLC that controls the cameras; a pneumatic system that ejects the defective trays; and a computer encharged only of analyzing every single image taken using a neuronal net. The developed model allows to detect the anomalies of the trays during the production with a very high accuracy, speed and effectiveness, leading to a very significant increase of the quality production.