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洪波, 戴江平, 李振凯, 王谦. 基于经验小波变换的磁控埋弧焊焊缝跟踪信号分析[J]. 焊接学报, 2017, 38(6): 37-40,46.
引用本文: 洪波, 戴江平, 李振凯, 王谦. 基于经验小波变换的磁控埋弧焊焊缝跟踪信号分析[J]. 焊接学报, 2017, 38(6): 37-40,46.
HONG Bo, DAI Jiangping, LI Zhenkai, WANG Qian. Signal analysis of magnetic control SAW seam tracking based on the empirical wavelet transform[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2017, 38(6): 37-40,46.
Citation: HONG Bo, DAI Jiangping, LI Zhenkai, WANG Qian. Signal analysis of magnetic control SAW seam tracking based on the empirical wavelet transform[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2017, 38(6): 37-40,46.

基于经验小波变换的磁控埋弧焊焊缝跟踪信号分析

Signal analysis of magnetic control SAW seam tracking based on the empirical wavelet transform

  • 摘要: 针对磁控埋弧焊跟踪信号非线性,不平稳及常用滤波方法难以滤除其相近低频干扰信号的缺点,提出一种基于经验小波变换(EWT)的磁控埋弧焊焊缝跟踪信号分析方法.该方法继承了EMD分解与小波变换各自的优点,分解出电弧跟踪信号的固有模态,在频域自适应地构造带通滤波器组从而构造正交小波函数,提取具有紧支撑傅立叶频谱的调幅-调频(AM-FM)成分.将此方法用于埋弧焊磁控电弧传感器焊缝跟踪平台信号分析中,提取出了更精确的焊缝跟踪信号,并通过试验验证了此方法的有效性及精确性.同时分析了相近低频噪声的信息,为进一步的信号处理及跟踪系统的优化提供了理论依据.

     

    Abstract: According to the the shortcomings of nonlinear tracking signal, unsteady and great difficulty of filtering out similar low frequency jamming signal when adopting the common filtering methods of magnetic control SAW seam tracking signal, a signal analytical method of magnetic control SAW seam tracking based on the EWT is proposed. This method possesses the advantages of the EMD decomposition and wavelet transform respectively. Firstly, this method can decompose the intrinsic modees of the arc tracking signal. Secondly, it constructs adaptive band-pass filters in the frequency domain so as to construct orthogonal wavelet functions. Finally, it can extract AM-FM components which with a compact support Fourier spectrum. When this method is used in the signal analysis of magnetic control SAW seam tracking platform, we could extract more detailed signal and verifyed the validity and accuracy of this method through the relevant experiment. In addition, the information of similar low frequency noise is also analyzed to provide a theoretical basis for further processing the signal and optimizing the tracking system.

     

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