Abstract
Due to the incipient fault attributes of gear are not obvious, So a hybrid diagnosis model to gear diagnosing based on Ensemble Empirical Mode Decomposition (EEMD) and Genetic-Support Vector Machine (GSVM) was proposed. With the method of EEMD,the gear vibration signals are adaptively decomposed into a finite number of Intrinsic Mode Function (IMF),which can alleviate model mixing that may appear in conventional EMD method. It calculates the energy character vectors of every IMF components,energy feature extracted from a number of IMFs that contained the most dominant fault information could serve as input genetic-vectors of support vector machine. The proposed model is applied to the gear testing system, and the results show that the diagnosis approach was effectively.
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