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Since several past decades, many studies prove that the statistical or signal features extracted from the sound acquired from laser welding process was significantly giving information on the weld condition. However, a considerable amount of studies were only emphasizing on the use of common statistical features in which it is restricted to some limitation when dealing with non-stationary random sound signal. In this particular work, the main aim was set to detect the irregularities along the weld bead by way of implementing the L-Statistic analysis on the acquired sound during pulse mode laser welding process. To achieve the goal, pulse mode laser welding have been done onto 22MnB5 boron steel plate in butt joined configuration. During the process, sound signal was acquired using microphone and further analyzed by extracting L-statistic features from it. According to the findings, among all the L-statistic features analyze in this study, L-Cv (scale) was found giving a significant indicator of the weld bead surface condition. Larger value of L-Cv was recorded at the point where the large underfill occurred. On the other hand, it was also found that the L-kurtosis values could give remarkable information on the existence of the irregularities on bead width and depth. Hence, it could be drawn into conclusion that the irregularities on the weld bead during the pulse mode laser welding could be detected from the appropriate L-statistic features of the acquired sound signal. The finding in this work was believed to be essential in enhancing the capability of acoustic sound method to be developed as online monitoring system for pulse mode laser welding process.

Detection of irregularities on weld bead from the L-Statistic analysis of the acquired sound during pulse mode laser welding process