Rotating machinery orbit analysis using complex wavelet transform
被引:0
作者:
Shen, T.
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机构:
Department of Power Engineering, Huazhong Univ. of Sci. and Technol., Wuhan, 430074, ChinaDepartment of Power Engineering, Huazhong Univ. of Sci. and Technol., Wuhan, 430074, China
Shen, T.
[1
]
Huang, S.
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机构:
Department of Power Engineering, Huazhong Univ. of Sci. and Technol., Wuhan, 430074, ChinaDepartment of Power Engineering, Huazhong Univ. of Sci. and Technol., Wuhan, 430074, China
Huang, S.
[1
]
Han, S.
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机构:
Department of Power Engineering, Huazhong Univ. of Sci. and Technol., Wuhan, 430074, ChinaDepartment of Power Engineering, Huazhong Univ. of Sci. and Technol., Wuhan, 430074, China
Han, S.
[1
]
Liu, D.
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机构:
Department of Power Engineering, Huazhong Univ. of Sci. and Technol., Wuhan, 430074, ChinaDepartment of Power Engineering, Huazhong Univ. of Sci. and Technol., Wuhan, 430074, China
Liu, D.
[1
]
机构:
[1] Department of Power Engineering, Huazhong Univ. of Sci. and Technol., Wuhan, 430074, China
来源:
Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis
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2000年
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20卷
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04期
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摘要:
A method is introduced for analyzing the axis orbit of a rotor by using the complex wavelet transform of a pair of vibration signals from two 90° positioned transducers atteched to the rotor. By the analysis of the relationship between scale parameter and vibration frequency, it can be seen that an examination of the amplitudes of the wavelet at a certain scale is equivalent to that of the periodogram at a certain range of frequency. The analysis of the orbits produced by two typical nonlinear faults, i.e. the friction and the crack, shows that the orbits contain different features for different faults. The high frequency components of the orbit due to the friction are unevenly spaced along the time axis in the time-frequency domain, whereas those due to the crack are even spaced, and its period is equal to the rotating period of the rotor. It is expected that the method proposed in the paper can be developed into a new and effective technology for fault monitoring and diagnosis due to its capability for the identification of detailed fault features.