The article attempts to detect the defects in friction stir welding (FSW) process by analyzing the signal acquired during welding. The said welding technique utilizes pressure and heat developed by the usage of a non-consumable tool. Thus, the axial force signal carries a lot of information about the physical process, and hence, it could be used to identify the weld defects. Signal analysis has been performed by using wavelet-based techniques. Before this analysis, a methodology has been followed to select the best mother wavelets suitable for the signal. The results of defect identification have been validated by mapping the processed signal with the actual weld quality.

本文试图通过分析焊接过程中获得的信号来检测搅拌摩擦焊（FSW）过程中的缺陷。所述焊接技术利用通过使用非消耗性工具而产生的压力和热量。因此，轴向力信号带有许多有关物理过程的信息，因此可以用来识别焊接缺陷。信号分析已通过使用基于小波的技术进行。在进行此分析之前，已遵循一种方法来选择适合信号的最佳母小波。通过将处理后的信号与实际焊接质量进行映射，可以验证缺陷识别的结果。