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Fault diagnosis of rolling bearings under variable speed conditions based on adaptive window rotation optimization short-time Fourier transform
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Yi-nan ZHAO1, Chang-feng YAN1, Jia-dong MENG2, Zong-gang WANG3, Hui-bin WANG1, 4, Li-xiao WU1
Journal of Vibration Engineering | 2024, 37(6) : 1064 - 1076
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Journal of Vibration Engineering | 2024, 37(6): 1064-1076
Fault diagnosis of rolling bearings under variable speed conditions based on adaptive window rotation optimization short-time Fourier transform
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Yi-nan ZHAO1, Chang-feng YAN1, Jia-dong MENG2, Zong-gang WANG3, Hui-bin WANG1, 4, Li-xiao WU1
Affiliations
  • 1School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730050, China
  • 2School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
  • 3College of Physics and Electromechanical Engineering, Hexi University, Zhangye 734000, China
  • 4Department of Medical Technology, Zhangzhou Health Vocational College, Zhangzhou 363000, China
Published: 2024-06-28 doi: 10.16385/j.cnki.issn.1004-4523.2024.06.017
Outline
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This paper proposes a fault diagnosis method for rolling bearings under variable speed conditions,based on the Adaptive Window Rotation Optimization Short-Time Fourier Transform (AWROSTFT). This method addresses the issue of low energy concentration caused by the fixed window effect in Short-Time Fourier Transform (STFT). Variational Mode Decomposition (VMD) is used to reduce the noise of the original vibration signal,and Particle Swarm Optimization (PSO) is employed to solve the complex problem of VMD parameter selection. A series of rotation operators are adaptively matched to the horizontal window in STFT using the tangent idea,aligning the rotation direction of the window with the instantaneous frequency modulation to improve the energy concentration of time-frequency representation. The instantaneous frequency,extracted by the spectral peak detection method,is divided by the frequency transformation curve. The result is matched with the fault characteristic coefficient of the bearing to achieve fault diagnosis of the rolling bearing under variable speed conditions. The results of simulation and experimental signals show that the proposed method effectively combines the advantages of PSO-VMD and AWROSTFT. Through the adaptive rotation window with the idea of tangency,the angle between the signal and the window function is globally reduced to zero,improving energy concentration,sharpening the time-frequency ridge line,and enabling fault diagnosis of rolling bearings under variable speed conditions.

fault diagnosis  /  time-frequency analysis  /  adaptive window rotation optimization short-time Fourier transform  /  VMD  /  variable speed conditions
Yi-nan ZHAO, Chang-feng YAN, Jia-dong MENG, Zong-gang WANG, Hui-bin WANG, Li-xiao WU. Fault diagnosis of rolling bearings under variable speed conditions based on adaptive window rotation optimization short-time Fourier transform[J]. Journal of Vibration Engineering, 2024 , 37 (6) : 1064 -1076 . DOI: 10.16385/j.cnki.issn.1004-4523.2024.06.017
Year 2024 volume 37 Issue 6
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Article Info
doi: 10.16385/j.cnki.issn.1004-4523.2024.06.017
  • Receive Date:2022-10-31
  • Online Date:2026-02-09
  • Published:2024-06-28
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  • Received:2022-10-31
  • Revised:2023-01-03
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Affiliations
    1School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730050, China
    2School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
    3College of Physics and Electromechanical Engineering, Hexi University, Zhangye 734000, China
    4Department of Medical Technology, Zhangzhou Health Vocational College, Zhangzhou 363000, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
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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