通过调节焊接电源的多组脉冲波形参数进行一系列焊接试验，对比并分析了脉冲电流峰值系数、脉冲电流峰值时间系数、脉冲电流基值系数、脉冲电流上升系数和脉冲电流下降系数发生改变后焊接电流信号的变化情况.采用集合经验模态分解(ensemble empirical mode decomposition, EEMD)方法对焊接过程中实时采集到的焊接电流信号进行分解，并对焊接电流信号和一系列本征模态函数(intrinsic mode function, IMF)进行时频域分析.随后，根据分析结果和焊缝表面形貌对焊接过程稳定性进行评估.结果表明，使用EEMD方法能够从焊接电流信号中分解出与短路过渡过程密切相关的特征IMF，稳定的焊接过程与不稳定的焊接过程相比，其特征IMF频谱分布区别明显，特征IMF频率分布范围越窄，焊接过程越稳定性，焊接飞溅越小，焊缝表面成形越好.
In this paper, a series of welding tests are carried out by adjusting the pulse waveform parameters of the welding power supply. Changes of the welding current signal are compared and analyzed after modifying pulse current peak coefficient, pulse current peak time coefficient, pulse current base value coefficient, pulse current rising coefficient and pulse current falling coefficient. Ensemble empirical mode decomposition (EEMD) method is adopted to decompose the welding current signal collected in real time during the welding process. The welding current signal and a series of intrinsic mode function (IMF) were analyzed in time-frequency domain. Then, the stability of welding process was evaluated according to the analysis results and weld surface morphology. The test results show that the EEMD method can be used to resolve the characteristic IMF closely related to the short-circuit transition process from the welding current signal. Compared with the unstable welding process, the characteristic IMF spectrum distribution is significantly different. The narrower the frequency distribution range of the characteristic IMF, the more stable the welding process, the smaller the welding splash, and the better the weld surface.
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