Automatic welding detection by an intelligent tool pipe inspection

C. J. Arizmendi, W. L. Garcia, M. A. Quintero

Resultado de la investigación: Artículos / NotasArtículo de la conferenciarevisión exhaustiva

7 Citas (Scopus)


This work provide a model based on machine learning techniques in welds recognition, based on signals obtained through in-line inspection tool called "smart pig" in Oil and Gas pipelines. The model uses a signal noise reduction phase by means of pre-processing algorithms and attribute-selection techniques. The noise reduction techniques were selected after a literature review and testing with survey data. Subsequently, the model was trained using recognition and classification algorithms, specifically artificial neural networks and support vector machines. Finally, the trained model was validated with different data sets and the performance was measured with cross validation and ROC analysis. The results show that is possible to identify welding automatically with an efficiency between 90 and 98 percent.

Idioma originalInglés
Número de artículo012082
PublicaciónJournal of Physics: Conference Series
EstadoPublicada - 9 jul. 2015
Evento11th International Conference on Damage Assessment of Structures, DAMAS 2015 - Ghent, Bélgica
Duración: 24 ago. 201526 ago. 2015


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