Feature Extraction of Weak Fault for Gear based on MOMEDA and Envelope Spectrum

Abstract

The gear weak fault signal is easy to be covered by the strong fault signal in a complex fault,and there will be missed diagnosis phenomenon. The the feature extraction of weak fault under gear complex failure is studied. Firstly,Multipoint Optimal Minimum Entropy Deconvolution Adjusted（ MOMEDA） is used as the pre-filter to denoise the original signal and enhance the periodic impact components in the signal. Then,the Hilbert transform is used to obtain the envelope spectrum. By analyzing the obvious frequency components to identify the fault,the extraction of weak fault characteristics is achieved. Simulation example of fault signal and transmission shows that this method can effectively realize the feature extraction of gear weak fault.

Keywords

• Gear;Multipoint optimal minimum entropy deconvolution adjusted;Weak fault;Feature extraction