Investigation on Time-Frequency Image Feature Extraction for Machine Condition Classification and Application

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Journal of Vibration and Shock ›› 2010, Vol. 29 ›› Issue (7) : 184-188.

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Investigation on Time-Frequency Image Feature Extraction for Machine Condition Classification and Application

Li Hong-Kun1,2;Zhou Shuai1;Huang Wenzong1

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Abstract

In this paper, a new machine condition pattern recognition method is introduced. Hilbert spectrum is used to construct time-frequency image for vibration signal analysis. Time frequency image gravity centre and information entropy are investigated to construct feature vector. Support vector machine is used as classification tool for pattern recognition. Rolling bearing pattern recognition is as an example to verify effectiveness of this method in the research. Multi-cycle synchronous average is used to reduce cyclostationary effect between different cycles to improve the recognition accuracy. According to the result analysis, it can be concluded that this method will contribute the development of machine fault diagnosis and pattern recognition.

Key words

Hilbert spectrum / Time-frequency image / Support Vector Machine / Synchronous average

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Li Hong-Kun;Zhou Shuai;Huang Wenzong. Investigation on Time-Frequency Image Feature Extraction for Machine Condition Classification and Application[J]. Journal of Vibration and Shock, 2010, 29(7): 184-188