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改进的VMD-ITD岩石声发射信号联合降噪方法

蔡改贫 李洋波 杨丽荣 黄祥海

蔡改贫,李洋波,杨丽荣, 等. 改进的VMD-ITD岩石声发射信号联合降噪方法[J]. 机械科学与技术,2023,42(8):1340-1348 doi: 10.13433/j.cnki.1003-8728.20220070
引用本文: 蔡改贫,李洋波,杨丽荣, 等. 改进的VMD-ITD岩石声发射信号联合降噪方法[J]. 机械科学与技术,2023,42(8):1340-1348 doi: 10.13433/j.cnki.1003-8728.20220070
CAI Gaipin, LI Yangbo, YANG Lirong, HUANG Xianghai. Improved VMD-ITD Joint Denoising Method for Rock Fracture Acoustic Emission Signals[J]. Mechanical Science and Technology for Aerospace Engineering, 2023, 42(8): 1340-1348. doi: 10.13433/j.cnki.1003-8728.20220070
Citation: CAI Gaipin, LI Yangbo, YANG Lirong, HUANG Xianghai. Improved VMD-ITD Joint Denoising Method for Rock Fracture Acoustic Emission Signals[J]. Mechanical Science and Technology for Aerospace Engineering, 2023, 42(8): 1340-1348. doi: 10.13433/j.cnki.1003-8728.20220070

改进的VMD-ITD岩石声发射信号联合降噪方法

doi: 10.13433/j.cnki.1003-8728.20220070
基金项目: 国家自然科学基金项目(51464017)、江西省重点研发计划项目(20181ACE50034)及江西省教育厅科学技术项目(GJJ190452)
详细信息
    作者简介:

    蔡改贫(1964−),教授,博士生导师,研究方向为智能矿山装备技术,智能监控与工业机器人,1123615286@qq.com

  • 中图分类号: TN911.4-34

Improved VMD-ITD Joint Denoising Method for Rock Fracture Acoustic Emission Signals

  • 摘要: 针对岩石破裂声发射信号具有非线性、非平稳以及大样本的特点和传统VMD、ITD算法对降噪处理时存在一定局限性的问题,提出一种改进VMD-ITD联合降噪方法。以钨岩为研究对象,首先采用分量能量比作为VMD的终止条件,将岩石破裂声发射信号分解得到多个IMF分量,将各分量与原始信号的互信息量作为各分量的加权因子进行重构信号,再对重构信号进行ITD分解以达到二次降噪的目的,最后以均方根误差与信噪比为去噪效果评价指标,对比分析VMD、ITD以及改进VMD-ITD联合降噪算法降噪效果。通过试验验证,改进VMD-ITD联合降噪算法在抑制非平稳信号噪声中,其均方根误差为4.552 1,信噪比为10.012 8。相比单一的VMD、ITD算法,降噪效果更好。
  • 图  1  联合降噪算法流程

    Figure  1.  Joint denoising algorithm flowchart

    图  2  加噪仿真信号及其频谱

    Figure  2.  A simulated noisy signal and its spectrum

    图  3  仿真信号的IMF

    Figure  3.  IMF of the simulated signal

    图  4  各IMF的频谱

    Figure  4.  Spectrum of each IMF

    图  5  二次降噪信号及其频谱

    Figure  5.  The second-order denoised signal and its spectrum

    图  6  万能材料试验系统

    Figure  6.  Universal material testing system

    图  7  传感器布局

    Figure  7.  Sensor layout

    图  8  钨岩岩样

    Figure  8.  Tungsten rock sample

    图  9  含噪原始信号及其频谱

    Figure  9.  Noise-containing original signal and its spectrum

    图  10  含噪原始信号的IMF

    Figure  10.  IMFs of the noise-containing original signal

    图  11  基于加权分量一次重构信号及其频谱

    Figure  11.  First-reconstructed signal using weighted components and the signal’s spectrum

    图  12  二次降噪重构信号及其频谱

    Figure  12.  Second denoised reconstructed signal and its spectrum

    表  1  各IMF与加噪仿真信号的互信息量

    Table  1.   Mutual Information between each IMF and the simulated noisy signal

    IMF序号 互信息量 IMF序号 互信息量
    1 0.068 6 0.179
    2 0.426 7 0.055
    3 0.415 8 0.048
    4 0.363 9 0.035
    5 0.591 10 0.026
    下载: 导出CSV

    表  2  3种算法降噪后信号的信噪比与均方根误差

    Table  2.   Signal-to-noise ratio (SNR) and root mean square error (RMSE) of the denoised signals using three algorithms

    降噪算法均方根误差信噪比
    VMD 1.1534 6.8562
    ITD 0.9003 10.2032
    (IP)VMD-ITD 0.1586 14.2877
    下载: 导出CSV

    表  3  传感器SR150M的基本参数

    Table  3.   Basic parameters of the sensors

    接收面材料频率范围/kHz谐振频率/kHz灵敏度峰值/dB
    陶瓷60 ~ 400150>75
    下载: 导出CSV

    表  4  各IMF与含噪原始信号的互信息量

    Table  4.   Mutual information between each IMF and the noise-containing original signal

    IMF序号 互信息量 IMF序号 互信息量
    1 0.6200 5 0.2156
    2 0.3548 6 0.2194
    3 0.2054 7 0.2252
    4 0.3084 8 0.2304
    下载: 导出CSV

    表  5  3种算法降噪后信号的信噪比与均方根误差

    Table  5.   Signal-to-noise ratio (SNR) and root mean square Error (RMSE) of the denoised signals using three algorithms

    降噪算法均方根误差信噪比
    VMD13.73525.3352
    ITD10.36717.5326
    (IP)VMD-ITD4.552110.0128
    下载: 导出CSV
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  • 收稿日期:  2021-08-01
  • 刊出日期:  2023-08-31

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