基于CEEMD与TQWT组合方法的爆破振动信号精细化特征提取

发布时间：2018-11-13 19:20

【摘要】：针对传统小波在爆破振动信号特征提取和分析方面的局限性,提出了基于CEEMD和TQWT组合的信号精细化特征提取方法。预先设定可调品质因子小波TQWT高、低品质因子参数对CEEMD分解优势分量重组信号进行分解,并引入相对权重因子θ,优化了分解过程,实现了爆破振动信号特征的精细化提取。分析结果表明:组合方法对爆破振动信号的分析不依赖于先验小波基的选择,分解过程实现了信号的二次滤波。通过连续小波多尺度三维谱和时频小波脊线对比,说明组合算法分解得到的最佳分析信号可真实反映振动信号的细节信息,时频分辨率更高。该组合方法抑制了杂波分量对信号特征的干扰,可精确地提取复杂环境下的爆破振动信号特征信息。
[Abstract]:Aiming at the limitation of traditional wavelet in feature extraction and analysis of blasting vibration signal, a signal refinement feature extraction method based on combination of CEEMD and TQWT is proposed. The adjustable quality factor wavelet TQWT with high and low quality factor parameters is pre-set to decompose the recombination signal of dominant component of CEEMD decomposition, and the relative weight factor 胃 is introduced to optimize the decomposition process, and the fine extraction of blasting vibration signal features is realized. The analysis results show that the combined method does not depend on the selection of prior wavelet basis for the analysis of blasting vibration signal, and the quadratic filtering of the signal is realized in the decomposition process. By comparing the continuous wavelet multi-scale three-dimensional spectrum with the time-frequency wavelet ridge, it is shown that the best analytical signal obtained by the combined algorithm can truly reflect the detailed information of the vibration signal, and the time-frequency resolution is higher. The combined method can suppress the interference of clutter components to the signal features and extract the characteristic information of blasting vibration signals in complex environment.
【作者单位】：中国矿业大学(北京)力学与建筑工程学院;
【基金】：国家自然科学基金面上资助(51274203) 高等学校学科创新引智计划(B14006)
【分类号】：TN911.7

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