基于软阈值的小波去噪方法在钢丝绳损伤检测中的研究

Yi Yao, Guoping Li, Xiangfang Zhang, Xinyi Teng, Mengsheng Huang
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引用次数: 2

摘要

针对传统的钢丝绳损伤电磁检测中采集到的信号中存在大量噪声的问题,提出了一种基于软阈值的小波去噪方法。通过比较不同小波基对检测信号去噪得到的信噪比,发现db4对检测信号去噪效果最理想。在实验中,对不同断丝检测信号进行去噪处理。实验结果表明,小波变换软阈值去噪方法是有效的,为后续特征值提取和定量识别的准确性提供了保证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Wavelet Denoising Method Based on Soft Threshold in Wire Rope Damage Detection
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.
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