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Application of the improved airspace wavelet denoising algorithm in friction welding ultrasonic testing signals

机译:改进的空域小波去噪算法在摩擦焊接超声检测信号中的应用

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In the process of ultrasonic flaw detection to friction welded joints, a number of weak-binding defects are difficult to be correctly detected due to noise pollution. This article studies the semi-soft threshold denoising method of spatial correlation coefficient based on the traditional spatial correlation coefficient de-noising method and threshold de-noising method, and come up with an improved airspace de-noising algorithm, which is used in the denoising of the defect signals. By comparing with hard thresholding, soft-threshold method and the traditional airspace algorithm on SNR and root mean square error, the detecting signals denoised by improved algorithm become more straight, and which better keep the sharp signal peak part of the curve about the original signals. So the identify characteristics of defect echo become more obvious, and we can get a smaller mean square error and the improved SNR of the reconstruction signals, which has the good de-noising effect and will lay a good foundation for the classification of defects next step.
机译:在对摩擦焊接头进行超声波探伤的过程中,由于噪声污染,难以正确检测出许多弱结合缺陷。本文基于传统的空间相关系数去噪方法和阈值去噪方法,研究了空间相关系数的半软阈值去噪方法,提出了一种改进的空域去噪算法,用于去噪。缺陷信号。通过与硬阈值,软阈值方法以及传统的空域算法在信噪比和均方根误差上的比较,改进算法去噪后的检测信号变得更直,并更好地保持了原始信号曲线的尖锐信号峰值部分。 。因此缺陷回波的识别特性更加明显,可以获得较小的均方误差和改善的重建信号的信噪比,具有良好的去噪效果,为下一步缺陷的分类奠定了良好的基础。 。

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