The wet multi-disc clutches are extensively used in various transmission systems,withone of the most prevalent failure modes being the buckling deformation of friction components.Animproved Hilbert-Huang transform met...The wet multi-disc clutches are extensively used in various transmission systems,withone of the most prevalent failure modes being the buckling deformation of friction components.Animproved Hilbert-Huang transform method(IHHT)is proposed to address the limitations of tradi-tional time-domain vibration analyses,such as low accuracy and mode mixing.This paper first clas-sifies the buckling degree of the friction components.Next,wavelet packet transform(WPT)isapplied to the vibration signals of different buckling plates to partition them into distinct fre-quency bands.Then,the instantaneous features are extracted by empirical mode decomposition(EMD)and Hilbert transform(HT)to discarding extraneous intrinsic mode function(IMF)com-ponents.Comparative analyses of Hilbert spectral entropy and time-domain features confirm theenhanced precision of IHHT under specific classifiers,which is better than traditional methods.展开更多
文摘The wet multi-disc clutches are extensively used in various transmission systems,withone of the most prevalent failure modes being the buckling deformation of friction components.Animproved Hilbert-Huang transform method(IHHT)is proposed to address the limitations of tradi-tional time-domain vibration analyses,such as low accuracy and mode mixing.This paper first clas-sifies the buckling degree of the friction components.Next,wavelet packet transform(WPT)isapplied to the vibration signals of different buckling plates to partition them into distinct fre-quency bands.Then,the instantaneous features are extracted by empirical mode decomposition(EMD)and Hilbert transform(HT)to discarding extraneous intrinsic mode function(IMF)com-ponents.Comparative analyses of Hilbert spectral entropy and time-domain features confirm theenhanced precision of IHHT under specific classifiers,which is better than traditional methods.
