An automatic welding defects classifier system
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Mostrar el registro completo del ítemGrupo de investigación
Grupo Diseño Electronico y Técnicas de Tratamiento de SeñalesFecha de publicación
2009-03-26Palabras clave
Inspección radiográficaDetección de defectos de soldadura
Técnicas de proceso de datos
Modelo neuronal
Arquitectura de redes
Resumen
Radiographic inspection is a well-established testing method to detect weld defects. However, interpretation of radiographic films is a difficult task. The reliability of such interpretation and the expense of training suitable experts have allowed that the efforts being made towards automation in this field. In this paper, we describe an automatic detection system to recognise welding defects in radiographic images. In a first stage, image processing techniques, including noise reduction, contrast enhancement, thresholding and labelling were implemented to help in the recognition of weld regions and the detection of weld defects. In a second stage, a set of geometrical features was proposed and extracted between defect candidates. In a third stage, an artificial neural network for weld defect classification was used under three regularisation process with different architectures. For the input layer, the principal component analysis technique was used in order to reduce the number of ...
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- Telecoforum 2008 [11]
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