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Research on Wavelet Denoising Method Based on Soft Threshold in Wire Rope Damage Detection

机译:基于钢丝绳损伤检测软阈值的小波去噪方法研究

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For traditional electromagnetic detection of steel wire rope damage, there are a lot of noise in the collected signals, and a wavelet denoising method based on soft threshold is proposed to apply to denoising. By comparing the signal-to-noise ratio obtained by using different wavelet bases to denoise the detection signal, it was found that db4 had the most ideal denoising effect on the detection signal. In the experiment, the detection signal of different broken wires was denoised. The experimental results show that the wavelet transform soft threshold denoising method is effective, which provides a guarantee for the subsequent feature value extraction and quantitative recognition accuracy.
机译:对于传统的钢丝绳损坏的传统电磁检测,收集信号中存在很多噪声,并提出了一种基于软阈值的小波去噪方法来施加去噪。通过比较通过使用不同小波碱获得的信噪比来去噪检测信号,发现DB4对检测信号具有最理想的去噪效果。在实验中,不同块线的检测信号被去噪。实验结果表明,小波变换软阈值去噪方法是有效的,为随后的特征值提取和定量识别准确性提供了一种保证。

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