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疲劳裂纹扩展声发射信号去噪盲分离

王兴路 贺利乐 贺瑞 石嘉堃 柴健湣

王兴路, 贺利乐, 贺瑞, 石嘉堃, 柴健湣. 疲劳裂纹扩展声发射信号去噪盲分离[J]. 机械科学与技术, 2021, 40(10): 1608-1613. doi: 10.13433/j.cnki.1003-8728.20200552
引用本文: 王兴路, 贺利乐, 贺瑞, 石嘉堃, 柴健湣. 疲劳裂纹扩展声发射信号去噪盲分离[J]. 机械科学与技术, 2021, 40(10): 1608-1613. doi: 10.13433/j.cnki.1003-8728.20200552
WANG Xinglu, HE Lile, HE Rui, SHI Jiakun, CAI Jianmin. Study on Denoising and Blind Separation of Fatigue Crack Propagation Acoustic Emission[J]. Mechanical Science and Technology for Aerospace Engineering, 2021, 40(10): 1608-1613. doi: 10.13433/j.cnki.1003-8728.20200552
Citation: WANG Xinglu, HE Lile, HE Rui, SHI Jiakun, CAI Jianmin. Study on Denoising and Blind Separation of Fatigue Crack Propagation Acoustic Emission[J]. Mechanical Science and Technology for Aerospace Engineering, 2021, 40(10): 1608-1613. doi: 10.13433/j.cnki.1003-8728.20200552

疲劳裂纹扩展声发射信号去噪盲分离

doi: 10.13433/j.cnki.1003-8728.20200552
基金项目: 

陕西省自然科学基础研究计划项目 2020JQ-908

陕西省教育厅专项科研计划项目 20JK0695

西安航空学院2020年省级大学生创新创业训练计划项目 S202011736079

详细信息
    作者简介:

    王兴路(1986-), 讲师, 博士, 研究方向为机械结构疲劳可靠性, wangxinglu816@163.com

  • 中图分类号: TN911;TH140

Study on Denoising and Blind Separation of Fatigue Crack Propagation Acoustic Emission

  • 摘要: 采用声发射技术评估疲劳裂纹扩展状态时,评估结论会受到其它类型声发射信号和噪声的干扰。针对上述问题,在分析经验模态分解和独立分量分析特点的基础上,提出集合导数优化经验模态分解与独立分量分析相结合的声发射信号去噪盲分离方法,用于疲劳裂纹扩展声发射信号的处理。分别进行模拟声发射信号和疲劳裂纹扩展试验,采用上述方法对采集声发射信号进行去噪盲分离,结果表明:基于集合导数优化经验模态分解与独立分量分析的声发射信号去噪方法可有效去除噪声信号的干扰,准确分离出疲劳裂纹扩展声发射信号,为进行含裂纹结构的疲劳损伤状态评估和剩余寿命预测奠定基础。
  • 图  1  EDEMD去噪原理图

    图  2  AE信号去噪盲分离流程

    图  3  无噪源信号的时域和频域波形

    图  4  含噪混合信号的时域和频域波形

    图  5  小波-ICA去噪盲分离结果

    图  6  EDEMD-ICA去噪盲分离结果

    图  7  单通道实测AE信号时域和频域波形

    图  8  基于EDEMD-ICA去噪盲分离分量

    表  1  AE信号主分量协方差特征值

    特征值 λ1 λ2 λ3 λ4 λ5 λ6 λ7 λ8
    数值 434.13 182.63 61.48 1.65 0.57 0.33 0.12 5.6×10-7
    下载: 导出CSV

    表  2  小波-ICA去噪盲分离波形相关系数

    小波-ICA s1(t)- s2(t)- s3(t)-
    相关系数 0.809 0.864 0.804
    下载: 导出CSV

    表  3  EDEMD-ICA去噪盲分离波形相关系数

    EDEMD-ICA s1(t)- s2(t)- s3(t)-
    相关系数 0.889 0.973 0.931
    下载: 导出CSV
  • [1] ZHENG X L, YAN J H, ZHAO K. Crack growth rate and cracking velocity in fatigue for a class of ceramics[J]. Theoretical and Applied Fracture Mechanics, 1999, 32(1): 65-73 doi: 10.1016/S0167-8442(99)00027-0
    [2] 王兴路, 贺利乐. 金属材料表面裂纹疲劳扩展形状演变规律[J]. 机械工程材料, 2019, 43(11): 57-61 doi: 10.11973/jxgccl201911013

    WANG X L, HE L L. Shape evolution rule of surface crack fatigue propagation of metallic materials[J]. Materials for Mechanical Engineering, 2019, 43(11): 57-61 (in Chinese) doi: 10.11973/jxgccl201911013
    [3] 史慧扬, 李海洋, 王召巴, 等. 广义S变换评价材料早期疲劳损伤的声发射信号处理技术[J]. 振动与冲击, 2020, 39(16): 244-253 https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ202016033.htm

    SHI H Y, LI H Y, WANG Z B, et al. Generalized S transform acoustic emission signal processing technology for early fatigue damage evaluation of materials[J]. Journal of Vibration and Shock, 2020, 39(16): 244-253 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ202016033.htm
    [4] MICHALCOVÁL, KADLEC M. Crack growth monitoring of CFRP composites loaded in different environmental conditions using acoustic emission method[J]. Procedia Engineering, 2015, 114: 86-93 doi: 10.1016/j.proeng.2015.08.045
    [5] 郭力, 霍可可. 断铅笔芯声发射实验信号研究[J]. 机电工程, 2018, 35(7): 663-667, 684 doi: 10.3969/j.issn.1001-4551.2018.07.001

    GUO L, HUO K K. Acoustic emission signal processing based on breaking lead test[J]. Journal of Mechanical & Electrical Engineering, 2018, 35(7): 663-667, 684 (in Chinese) doi: 10.3969/j.issn.1001-4551.2018.07.001
    [6] 史慧扬, 李海洋, 王召巴, 等. 基于小波包能量谱的声发射信号处理技术[J]. 测试技术学报, 2019, 33(3): 201-208 doi: 10.3969/j.issn.1671-7449.2019.03.004

    SHI H Y, LI H Y, WANG Z B, et al. Acoustic emission signal processing technology based on wavelet packet energy spectrum[J]. Journal of Test and Measurement Technology, 2019, 33(3): 201-208 (in Chinese) doi: 10.3969/j.issn.1671-7449.2019.03.004
    [7] 孙守保, 郭瑜, 伍星. 基于声发射信号的滚动轴承外圈疲劳剥落故障双冲击特征提取[J]. 振动与冲击, 2017, 36(4): 1-6, 20 https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ201704001.htm

    SUN S B, GUO Y, WU X. Double impulse phenomenon extraction of outer race spalled rolling element bearings based on acoustic emission signals[J]. Journal of Vibration and Shock, 2017, 36(4): 1-6, 20 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ201704001.htm
    [8] 张泽宇, 惠记庄, 石泽. 小波包最优基分解树的降噪滤波方法研究[J]. 机械科学与技术, 2020, 39(1): 28-34 doi: 10.13433/j.cnki.1003-8728.20190239

    ZHANG Z Y, HUI J Z, SHI Z. Research on denoising and filtering method based on wavelet packet optimal base decomposition tree[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(1): 28-34 (in Chinese) doi: 10.13433/j.cnki.1003-8728.20190239
    [9] MERCORELLI P. A denoising procedure using wavelet packets for instantaneous detection of pantograph oscillations[J]. Mechanical Systems and Signal Processing, 2013, 35(1-2): 137-149 doi: 10.1016/j.ymssp.2012.09.001
    [10] CHU P C, FAN C W, HUANG N. Derivative-optimized empirical mode decomposition for the Hilbert-Huang transform[J]. Journal of Computational and Applied Mathematics, 2014, 259: 57-64 doi: 10.1016/j.cam.2013.03.046
    [11] 于金涛, 赵树延, 王祁. 基于经验模态分解和小波变换声发射信号去噪[J]. 哈尔滨工业大学学报, 2011, 43(10): 88-92 doi: 10.11918/j.issn.0367-6234.2011.10.019

    YU J T, ZHAO S Y, WANG Q. De-nosing of acoustic emission signals based on empirical mode decomposition and wavelet transform[J]. Journal of Harbin Institute of Technology, 2011, 43(10): 88-92 (in Chinese) doi: 10.11918/j.issn.0367-6234.2011.10.019
    [12] 毋文峰, 陈小虎, 苏勋家. 基于经验模式分解的单通道机械信号盲分离[J]. 机械工程学报, 2011, 47(4): 12-16 https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201104004.htm

    WU W F, CHEN X H, SU X J. Blind source separation of single-channel mechanical signal based on empirical mode decomposition[J]. Journal of Mechanical Engineering, 2011, 47(4): 12-16 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201104004.htm
    [13] 李晶皎, 安冬, 王骄. 基于EEMD和ICA的语音去噪方法[J]. 东北大学学报, 2011, 32(11): 1554-1557 doi: 10.12068/j.issn.1005-3026.2011.11.009

    LI J J, AN D, WANG J. Speech denoising method based on the EEMD and ICA approaches[J]. Journal of Northeastern University, 2011, 32(11): 1554-1557 (in Chinese) doi: 10.12068/j.issn.1005-3026.2011.11.009
    [14] CHAI M Y, ZHANG Z X, DUAN Q. A new qualitative acoustic emission parameter based on Shannon's entropy for damage monitoring[J]. Mechanical Systems and Signal Processing, 2018, 100: 617-629 doi: 10.1016/j.ymssp.2017.08.007
    [15] BOUDRAA A O, CEXUS J C. EMD-based signal filtering[J]. IEEE Transactions on Instrumentation and Measurement, 2007, 56(6): 2196-2202 doi: 10.1109/TIM.2007.907967
    [16] ALBARBAR A, GU F, BALL A D. Diesel engine fuel injection monitoring using acoustic measurements and independent component analysis[J]. Measurement, 2010, 43(10): 1376-1386 doi: 10.1016/j.measurement.2010.08.003
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出版历程
  • 收稿日期:  2020-07-21
  • 刊出日期:  2021-10-01

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