Detection of defects on weld bead through the wavelet analysis of the acquired arc sound signal

• DOI: 10.15282/jmes.10.2.2016.8.0192
• Publication Date: 2025-03-14T04:52:29Z
• Authors: M.F.M. Yusof; M.A. Kamaruzaman; M. Zubair; M. Ishak
• Keywords: SIGNAL (programming language); Bead

Recently, the development of online quality monitoring system based on arc sound signal has become one main interests due its ability to provide non-contact measurement. Notwithstanding, numerous unrelated-to-defect sources which influence generation are aspects that increase difficulties applying this method detect defect during welding process. This work aims reveal hidden information associates with existence irregularities and porosity weld bead from acquired by discrete wavelet transform. To achieve aim, was captured metal inert gas (MIG) process three API 5L X70 steel specimens. Prior acquisition process, frequency range set 20 Hz 10 000 is in audible range. In next stage, a transform applied order associated occurrence discontinuity porosity. According results, it clear not giving an obvious indication presence as well location high noise level. More interesting findings have been obtained when (DWT) analysis applied. The results indicate level 8 approximate detail coefficient given significant sign respectively. Moreover, despite surfaces pores, found give sub-surface formation Hence, could be concluded respect