基于小波消噪与LMD的埋弧焊交流方波电弧信息提取

Feature Extraction of AC Square Wave SAW Arc Characteristics Based on Wavelet Packet Denoising and LMD

埋弧焊交流方波电弧电信号存在畸变,影响焊接过程电弧稳定性和焊缝成形质量,针对于此,在对采集的埋弧焊交流方波电弧电流信号进行小波包降噪后,利用局部均值分解(local mean decomposition,LMD)对电弧电流信号进行自适应分解,获得若干个具有真实物理意义的PF(product function)分量,并对PF分量集进行Hilbert变换及能量熵计算。结果表明,利用小波消噪与LMD能有效得到埋弧焊交流方波电流波形畸变的不同频率成分及其幅值在时间特征尺度上的变化特征,在此基础上通过Hilbert变换及能量熵计算可以有效提取反映焊接过程电弧稳定性和焊缝成形质量的电弧特征信息。

In order to extract the arc feature information associated with welding quality in alterna- ting current square wave submerged arc welding（AC square wave SAW）,a LMD method combining with the wavelet packet transform was put forward. After performing wavelet packet denoising, the LMD was used to decompose the collected current signals into a number of product functions（PFs）, and then the PFs were selected for the Hilbert transform and energy entropy calculation. Application of wavelet denoising and LMD can get the vaild waveform distortion of different frequency components effectively and the amplitude variation characteristics in the time scale. On the basis of that,the Hil- bert transform and energy entropy calculation can be used to extracte arc characteristics effectively. Experimental results show the effectiveness of this approach to extract the arc physical information re- lated to welding quality.