Application Of Improved VMD And Wavelet Threshold Denoising Method In Bolt Detection

Yi-ming Liu
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Abstract

Rock bolts are often used for reinforcement of slopes, tunnels, and mines in transportation, water conservancy, coal mining and other industries. Thus, identifying the quality of rock bolts is important. To address the difficult of obtaining useful information on rock bolts in complex environment, this study proposes a noise reduction method based on the combination of improved variational mode decomposition (VMD) and wavelet threshold denoising (WTD) method. In this method, the number of decomposition modes in improved VMD algorithm is determined by weighted kurtosis values. First, the electromagnetic ultrasonic signal is decomposed into a finite number of intrinsic mode functions (IMFs) through improved VMD. Second, noisy and invalid IMF components are removed according to weighted kurtosis values. Finally, the residual IMF components are used to reconstruct signal and wavelet threshold processing to improve denoising effect. This VMDWTD method is applied in both simulation signal and magnetostrictive guided wave signal. The results showed that the method retained more valid information and had better noise reduction effect than ensemble empirical mode decomposition with WTD and traditional WTD method.
改进VMD和小波阈值去噪方法在螺栓检测中的应用
锚杆常用于交通、水利、煤矿等行业的边坡、隧道、矿山的加固。因此,确定锚杆的质量是很重要的。针对复杂环境下锚杆信息难以获取的问题,提出了一种基于改进变分模态分解(VMD)和小波阈值去噪(WTD)相结合的锚杆降噪方法。在该方法中,改进的VMD算法的分解模式数由加权峰度值决定。首先,通过改进的VMD将电磁超声信号分解为有限个本征模态函数(IMFs);其次,根据加权峰度值去除IMF的噪声和无效分量。最后利用残差IMF分量重构信号并进行小波阈值处理,提高去噪效果。该方法在仿真信号和磁致伸缩导波信号中均有应用。结果表明,该方法比WTD集成经验模态分解方法和传统WTD方法保留了更多的有效信息,具有更好的降噪效果。
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