94 / 2021-07-21 22:21:32

Multi-scale mode denoising method for weak gear fault feature extraction

The characteristics caused by gear fault is often submerged by the strong noise inference, which brings difficulties for weak fault feature identification in the early fault stage. Especially, the desired weak features would be modulated into several frequency bands, and this will also weaken the effect of the fault information identification. Motived by these issues, this paper proposed a multi-scale mode denoising method to extract and enhance early weak gear fault signals. In this method, the raw vibration signal collected is decomposed into a series of band-limited intrinsic mode functions by variational mode decomposition, and then the sensitive modes including rich periodic amplitude modulation information are selected via proposed syncretic modulated impact index. And then, the denoised signal is obtained by reconstruction from the sub-signals, which are generated from sensitive modes using minimum entropy deconvolution to extract fault feature. Finally, the fault feature can be identified clearly in the envelope spectrum of deonised signal. The simulation and experimental results illustrate that this method can effectively extract and enhance the weak fault features of gear