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Statistical Feature of Hilbert - Huang Transform and Its Application in Aeroengine Vibration Analysis
WU Ya-hui;LI Xin-liang;HONG Bao-ling;ZHANG Da-zhi
2012, 32 (1):
113-118.
DOI: 10.3969/j.issn.1006-1355-2012.01.027
The vibration signals of the aeroengine include many multi-frequency components and noise components. In this paper, the Hilbert-Huang transform is used to decompose the vibration signals into a number of intrinsic mode functions (IMF) which represent different physical meanings of the data. Then, the generalized roughness vector of the IMF weighted by its energy is extracted from the IMF signals. Finally, as the fault characteristic vectors, the derived parameters are input into the support vector machine (SVM) classifier and the working conditions and fault patterns are identified by the output of the classifier. Results from the analysis of aeroengine vibration signals show that this fault diagnosis method can classify the working conditions and the fault patterns effectively.
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