Abstract
AE (acoustic emission) signals generated in laser welding were studied using wavelet time-frequency signal analysis methods. The AE signals were decomposed into a series of discrete sequences distributed over different frequency bands through wavelet transform. Further data processing was then carried out after selecting several decomposition sequences consistent with specific research goals. More detailed information of the welding process can be revealed through analyzing the time-frequency properties of the AE signals than can be obtained through statistical analysis or simple magnitude measurements. There is a significant difference between the AE signal from the desired deep-penetration weld and that which is acquired when there are problems with misalignment and excessive joint gap. The intensity of low-frequency (<781 Hz) components of the AE signals is dramatically reduced when welding defects occur. The same phenomena are found in the oscillation amplitude of frequency components between 781 and 1562 Hz. Based on the detailed information obtained from AE signals via wavelet analysis, a signal intensity moving average (IMA) curve is defined in this article. The curve is an effective tool for recognizing transitions of welding states and identifying defects quickly and reliably. The potential application of the IMA curve is also described in this article.
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