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Time-frequency Analysis of Non-Stationary Vibration Signals based on EP-CEEMDAN Algorithm
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Miao SUN1, 2, 3, Ling QU4, Li-ping YUAN1, Jing WU2, 3, 5, Yu-guang SHEN1
Blasting | 2024, 41(4) : 150 - 155
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Blasting | 2024, 41(4): 150-155
• BLASTING SAFETY •
Time-frequency Analysis of Non-Stationary Vibration Signals based on EP-CEEMDAN Algorithm
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Miao SUN1, 2, 3, Ling QU4, Li-ping YUAN1, Jing WU2, 3, 5, Yu-guang SHEN1
Affiliations
  • 1.College of Environment and Engineering, Hubei Land Resources Vocational College, Wuhan 430090, China
  • 2.Engineering Research Center of Rock-soil Drilling & Excavation and Protection, Ministry of Education of China University of Geosciences, Wuhan 430074, China
  • 3.Hubei Small Town Development Research Center, Xiaogan 432000, China
  • 4.Geophysical Exploration Brigade of Hubei Geological Bureau, Wuhan 430056, China
  • 5.Faculty of Civil Engineering, Hubei Engineering University, Xiaogan 432000, China
Published: 2024-12-01 doi: 10.3963/j.issn.1001-487X.2024.04.019
Outline
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The intrinsic mode confusion of empirical mode decomposition (EMD) and the ensemble empirical mode decomposition (EEMD) can only suppress mode confusion to a limited extent, as the white noise added by EEMD cannot be fully neutralized, which compromises the completeness of the original signal. Additionally, both methods fail to avoid interference from endpoint effects. Modal confusion and endpoint effects lead to distortions in the time-frequency analysis results obtained from the Hilbert transforms of EMD and EEMD. A complete ensemble empirical mode decomposition with adaptive noise and endpoint processing (EP-CEEMDAN) is proposed to address these issues. Simulation experiments were conducted to compare EMD, EEMD, and EP-CEEMDAN decomposition results on simulated vibration signals. Through multiscale permutation entropy detection and marginal spectral analysis, it was verified that EP-CEEMDAN has better control over endpoint effects and mode confusion, proving that EP-CEEMDAN is a more effective adaptive algorithm than EMD and EEMD. Finally, EP-CEEMDAN was applied to the processing of measured non-stationary vibration signals, where adaptive white noise was added at the endpoints of the vibration signals during each stage of decomposition. The method successfully generated various intrinsic mode functions (IMF) by calculating a unique residual signal. The EP-CEEMDAN algorithm effectively suppresses IMF endpoint divergence and modal confusion, while the time-frequency spectrum obtained through the Hilbert transform offers high resolution in both time and frequency domains. This result can be used for vibration feature recognition in non-stationary vibration signals.

empirical mode decomposition  /  complete ensemble empirical mode decomposition with adaptive noise  /  mode mixing  /  endpoint effect  /  Hilbert transform
Miao SUN, Ling QU, Li-ping YUAN, Jing WU, Yu-guang SHEN. Time-frequency Analysis of Non-Stationary Vibration Signals based on EP-CEEMDAN Algorithm[J]. Blasting, 2024 , 41 (4) : 150 -155 . DOI: 10.3963/j.issn.1001-487X.2024.04.019
Funding
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  • Hubei Provincial Natural Science Foundation of China(2022CFB334; 2022CFB948)
  • Engineering Research Center of Rock-soil Drilling & Excavation and Protection, Ministry of Education(202404; 202409)
  • Hubei Provincial Department of Education Scientific Research Program Guidance Project(B2022602)
  • Hubei Small Town Development Research Center Fund(2024A004)
Appendix
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Year 2024 volume 41 Issue 4
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91
38
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Article Info
doi: 10.3963/j.issn.1001-487X.2024.04.019
  • Receive Date：2023-08-02
  • Online Date：2026-03-19
  • Published：2024-12-01
Article Data
Affiliations
History
  • Received：2023-08-02
Funding
Hubei Provincial Natural Science Foundation of China(2022CFB334; 2022CFB948)
Engineering Research Center of Rock-soil Drilling & Excavation and Protection, Ministry of Education(202404; 202409)
Hubei Provincial Department of Education Scientific Research Program Guidance Project(B2022602)
Hubei Small Town Development Research Center Fund(2024A004)
Affiliations
    1.College of Environment and Engineering, Hubei Land Resources Vocational College, Wuhan 430090, China
    2.Engineering Research Center of Rock-soil Drilling & Excavation and Protection, Ministry of Education of China University of Geosciences, Wuhan 430074, China
    3.Hubei Small Town Development Research Center, Xiaogan 432000, China
    4.Geophysical Exploration Brigade of Hubei Geological Bureau, Wuhan 430056, China
    5.Faculty of Civil Engineering, Hubei Engineering University, Xiaogan 432000, China

Corresponding:

QU Ling (1983-), female, born in Qufu, Shandong Province, Ph. D, engineer, mainly engaged in ocean, engineering, and other data processing algorithms, (E-mail) .
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表12种不同金属材料的力学参数
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多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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