基于ICEEMDAN-ICA的焊缝信号去噪算法

    Weld Signal Denoising Algorithm for Welds Based on ICEEMDAN-ICA

    • 摘要: 随着视觉传感器在焊缝识别领域的应用,基于线阵电荷耦合元件(CCD)的焊缝识别技术以其成本低、实时性好等优势受到广泛关注,但其准确度往往与滤波技术密切相关。为此,提出基于ICEEMDAN-ICA的焊缝信号去噪算法,首先利用线阵CCD采集焊板的焊缝灰度图像,然后通过改进完备经验模态分解(ICEEMDAN)和独立成分分析(ICA)算法得到焊缝信号的多个源信号,通过模糊熵阈值判据识别并剔除其中的噪声源信号,最后重构得到焊缝滤波信号。实验结果表明,该算法能更好去除焊接信号的高频噪声,保留其中的有效信息。

       

      Abstract: With the application of visual sensor in the field of welding seam identification, the welding seam identification technology based on linear array charge coupled devices(CCD) has attracted wide attention due to its advantages such as low cost and good real-time performance, but its accuracy is often closely related to the filtering technology. Therefore, the weld signal denoising algorithm based on ICEEMDAN-ICA was proposed. Firstly, the weld grey image was acquired by using the linear CCD first, and then multiple source of weld signals was obtained by by improved complementary ensemble empirical mode decomposition with adaptive noise and independent component analysis algorithm,the noise signal was identified and eliminated through the fuzzy entropy threshold criterion, finally the weld filtering signal was reconstructed. The experimental results show that this algorithm can remove the high frequency noise of welding signal and retain the effective information.

       

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