Application of SVM models for classification of welded joints (CROSBI ID 268712)
Prilog u časopisu | prethodno priopćenje | međunarodna recenzija
Podaci o odgovornosti
Marić, Dejan ; Duspara, Miroslav ; Šolić, Tomislav ; Samardžić, Ivan
engleski
Application of SVM models for classification of welded joints
Classification algorithm based on the support vector method (SVM) was used in this paper to classify welded joints in two categories, one being good (+1) and the other bad (−1) welded joints. The main aim was to classify welded joints by using recorded sound signals obtained within the MAG welding process, to apply appropriate preprocessing methods (filtering, processing) and then to analyze them by the SVM. This paper proves that machine learning, in this specific case of the support vector methods (SVM) with appropriate input conditions, can be efficiently applied in assessment, i.e. in classification of welded joints, as in this case, in two categories. The basic mathematical structure of the machine learning algorithm is presented by means of the support vector method.
Classification ; machine learning ; sound signal ; SVM model ; welding
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Podaci o izdanju
26 (2)
2019.
533-538
objavljeno
1330-3651
1848-6339
10.17559/TV-20180305095253