【摘要】 隧道钻爆施工中工序的平行、搭接、交叉及其组合方式的实施，使实测爆破振动信号中存在的较多噪声干扰影响频带及能量分布特征分析的准确性。为获得真实爆破振动特性，提出一种基于混沌映射的麻雀搜索算法-变分模态分解-多尺度排列熵(sparrow search algorithm-variational mode decomposition-multi-scale permutation entropy, SSA-VMD-MPE)(r)滤波重构振动信号降噪方法。该方法首先采用基于混沌映射的SSA对VMD关键参数模态数K和惩罚因子α进行寻优；然后将分解所得各固有模态函数进行MPE与相关系数r检验，依据双控制指标将其划分为真实信号、噪声及含噪信号分量；最后对含噪信号分量进行低通滤波处理后与真实信号分量共同重构得到降噪信号。对实测隧道爆破振动信号处理表明，该方法减少了人为因素对VMD的影响，提高了信号分解的自适性和准确性，在较好去除高频噪声成分的同时对低频振动能量影响较小，有效保留了爆破振动真实信号成分，可重构出高信噪比、低重构误差的降噪信号，降噪效果良好。更多还原

【Abstract】 The implementation of parallel, overlapping, intersecting and their combination methods in tunnel drilling and blasting construction introduces significant noise interference in measured blasting vibration signals, which affects the correctness of frequency band and energy distribution feature analysis. Here, to obtain true blasting vibration characteristics, the sparrow search algorithm-variational mode decomposition-multi-scale permutation entropy(SSA-VMD-MPE)(r)filtering reconstruction vibration signal denoising method was proposed based on chaotic mapping. Firstly, this method could use SSA based on chaotic mapping to optimize key parameters of VMD of modal number K and penalty factor α. Then, decomposed intrinsic mode function of original vibration signal were tested with MPE and correlation coefficient r, and classified into real signal, noise and noisy signal components based on dual control indexes. Finally, noisy signal components were low-pass filtered and reconstructed together with real signal components to obtain noise reduction signal. Processing actual tunnel blasting vibration signals showed that the proposed method can reduce effects of human factors on VMD, improve the adaptability and correctness of signal decomposition, effectively remove high-frequency noise components and minimize effects on low-frequency vibration energy; it can effectively preserve real signal components of blasting vibration and reconstruct noise reduction signals with high signal-to-noise ratio and low reconstruction error, the denoising effect is good.更多还原