基于CEEMDAN-K-means算法的爆破振动信号去噪研究

Blasting Vibration Signal Denoising based on CEEMDAN-K-means Algorithm

针对实测爆破振动信号存在噪声和CEEMDAN方法在去噪过程中容易造成信息缺失的问题,考虑聚类分析方法具有良好的数据处理能力,依据分解—聚类—重构的思想,提出了CEEMDAN-K-means算法的爆破振动信号去噪方法。首先,该方法通过CEEMDAN方法分解爆破振动信号获得不同数量级的IMF分量;然后,利用K-means聚类分析算法将IMF分量为五个不同类别并采用方差贡献率校核;最后,剔除高频噪声类别的IMF分量,获得重构的纯净爆破振动信号。以某露天矿爆破振动信号为例,采用信噪比和均方根误差指标,评价了CEEMDAN-K-means算法信号去噪性能。研究结果表明:与CEEMDAN方法和EMD-小波阈值方法相比,CEEMDAN-K-means信号去噪方法信噪比(20.06 dB)最大,分别提高了1.26 dB和7.7 dB,均方根误差(0.22×10^(-3))最小,说明该方法不仅具有良好的信号去噪效果,也具有较好的保真度。通过对比分析不同方法信号去噪效果可知,在有效保留真实信号成分的基础上,CEEMDAN-K-means方法可以有效去除实测爆破振动信号包含的高频成分,在爆破振动信号去噪领域具有实用性和有效性,为爆破振动信号去噪方法研究提供了新思路。

In view of the problem of noise and information loss in the CEEMDAN method in the denoising process of actual measurement blasting vibration signals,the clustering analysis method is considered to have good data processing ability.Based on the idea of decomposition-clustering-reconstruction,CEEMDAN-K-means algorithm for denoising of blasting vibration signals is proposed.Firstly,this method decomposes the blasting vibration signal by CEEMDAN method to obtain IMF components of different quantity levels.Then,the K-means clustering analysis algorithm is used to classify the IMF components into five different categories,and variance contribution rate verification is used.Finally,the IMF components of high frequency noise category are removed and the reconstructed pure blasting vibration signal is obtained.Taking the blasting vibration signals from an open-pit mine as example,the signal denoising performance of the CEEMDAN-K-means algorithm was evaluated by signal-to-noise ratio and root mean square error indexes.The research results show that compared with the CEEMDAN method and the EMD-wavelet threshold method,the CEEMDAN-K-means signal denoising method has the largest signal-to-noise ratio(20.06 dB),which is increased by 1.26 dB and 7.7 dB,respectively,and the smallest root mean square error(0.22 10^(-3)),indicating that the method not only has good denoising effect,but also has good fidelity.Through the comparison and analysis of the denoising effect of different methods,it is known that on the basis of effectively retaining the real signal component,the CEEMDAN-K-means method can effectively remove the high-frequency components contained in the measured blasting vibration signal,and has practicality and effectiveness in the field of blasting vibration signal denoising.