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Automatic quality inspection of percussion cap mass production by means of 3D machine vision and machine learning techniques

  • A. Tellaeche*
  • , R. Arana
  • , A. Ibarguren
  • , J. M. Martínez-Otzeta
  • *Autor correspondiente de este trabajo
  • TEKNIKER

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

The exhaustive quality control is becoming very important in the world's globalized market. One of these examples where quality control becomes critical is the percussion cap mass production. These elements must achieve a minimum tolerance deviation in their fabrication. This paper outlines a machine vision development using a 3D camera for the inspection of the whole production of percussion caps. This system presents multiple problems, such as metallic reflections in the percussion caps, high speed movement of the system and mechanical errors and irregularities in percussion cap placement. Due to these problems, it is impossible to solve the problem by traditional image processing methods, and hence, machine learning algorithms have been tested to provide a feasible classification of the possible errors present in the percussion caps.

Idioma originalInglés
Título de la publicación alojadaHybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings
Páginas270-277
Número de páginas8
EdiciónPART 1
DOI
EstadoPublicada - 2010
Publicado de forma externa
Evento5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010 - San Sebastian, Espana
Duración: 23 jun 201025 jun 2010

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NúmeroPART 1
Volumen6076 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010
País/TerritorioEspana
CiudadSan Sebastian
Período23/06/1025/06/10

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