上海交通大学学报 ›› 2023, Vol. 57 ›› Issue (12): 1648-1656.doi: 10.16183/j.cnki.jsjtu.2022.255

所属专题: 《上海交通大学学报》2023年“船舶海洋与建筑工程”专题

• 船舶海洋与建筑工程 • 上一篇    

改进希尔伯特-黄变换含噪振动信号时频分析

孙苗1,3, 杨钧凯2, 吴立3,4()   

  1. 1.湖北国土资源职业学院 环境与工程学院,武汉 430090
    2.武汉华中科大建筑规划设计研究院有限公司,武汉 430070
    3.中国地质大学(武汉) 岩土钻掘与防护教育部工程研究中心,武汉 430074
    4.中国地质大学(武汉) 工程学院, 武汉 430074
  • 收稿日期:2022-07-05 修回日期:2022-11-01 接受日期:2022-11-10 出版日期:2023-12-28 发布日期:2023-12-29
  • 通讯作者: 吴 立,教授,博士生导师;E-mail: lwu@cug.edu.cn.
  • 作者简介:孙 苗(1993-),讲师,主要从事爆破地震波信号处理研究.
  • 基金资助:
    国家自然科学基金(41672260);岩土钻掘与教育部工程研究中心(202215);湖北省教育厅科学研究计划指导性项目(B2022602)

Time-Frequency Analysis of Noisy Vibration Signal Based on Improved Hilbert-Huang Transform

SUN Miao1,3, YANG Junkai2, WU Li3,4()   

  1. 1. College of Environment and Engineering, Hubei Land Resources Vocational College, Wuhan 430090, China
    2. Wuhan Huazhong University of Science and Technology Architectural Planning and Design Institute Co., Ltd., Wuhan 430070, China
    3. Engineering Research Center of Rock-Soil Drilling & Excavation and Protection of the Ministry of Education, China University of Geosciences, Wuhan 430074, China
    4. Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
  • Received:2022-07-05 Revised:2022-11-01 Accepted:2022-11-10 Online:2023-12-28 Published:2023-12-29

摘要:

针对希尔伯特-黄变换(Hilbert-Huang Transform, HHT)含噪振动信号时频分析产生的模态混淆和瞬时频率缺乏实际意义的现象,改进经验模态分解(EMD)得到自适应补充集合经验模态分解(CEEMDAN)后,结合多尺度排列熵(MPE)抑制EMD模态混淆,再改进Hilbert变换得到改进归一化Hilbert变换(INHT),最终形成CEEMDAN·MPE-INHT.为验证CEEMDAN·MPE-INHT含噪振动信号时频分析的准确性,进行EMD-HT、EEMD-NHT、CEEMDAN-INHT、CEEMDAN·MPE-INHT含噪仿真振动信号时频分析对比研究.研究结果表明:CEEMDAN能够控制低频噪声;MPE能抑制高频噪声;INHT使Hilbert变换不受Bedrosian定理约束.最后将CEEMDAN·MPE-INHT算法用于实际工程含噪振动信号时频分析中,CEEMDAN·MPE分解得到的固有模态函数(IMF)经INHT处理得到的时频谱在时域和频域上都具有较高的分辨率,可提高时频特征参数提取精度,有助于振动信号危害控制.

关键词: 经验模态分解, 希尔伯特变换, 模态混淆, 固有模态函数

Abstract:

Aimed at the phenomenon of modal confusion and lack of practical significance of instantaneous frequency caused by Hilbert-Huang transform (HHT) noisy vibration signal time-frequency analysis, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is obtained by improving empirical mode decomposition (EMD), and in combination with multiscale permutation entropy (MPE) to suppress EMD modal confusion. At the same time, improved normalized Hilbert transform(INHT) is obtained by improving Hilbert transform, and finally the CEEMDAN·MPE-INHT time-frequency analysis algorithm is formed. In order to verify the accuracy of time-frequency analysis of CEEMDAN·MPE-INHT noisy vibration signals, a comparative study of time-frequency analysis of EMD-HT, EEMD-NHT, CEEMDAN-INHT and CEEMDAN·MPE-INHT noisy simulation vibration signals is conducted. The results show that CEEMDAN can control low frequency noise; MPE can suppress high frequency noise; INHT can make Hilbert transform not constrained by Bedrosian theorem. Finally, CEEMDAN·MPE-INHT algorithm is applied to the time-frequency analysis of noisy vibration signals in practical engineering. The time spectrum of intrinsic mode function (IMF) decomposed by CEEMDAN·MPE after INHT processing has a high resolution in time domain and frequency domain, which can improve the extraction accuracy of time-frequency characteristic parameters and help control the harm of vibration signals.

Key words: empirical mode decomposition, Hilbert transform, modal confusion, intrinsic mode function

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