Jixie chuandong (Jan 2018)
Condition Identification of Gears based on CEEMDAN Energy Entropy
Abstract
The Ensemble Empirical Mode Decomposition（EEMD） often encounters two difficulies in removing the added white noise residing in extracted components and easy production of spurious modes. Aiming at the deficiencies in the EEMD,the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise（CEEMDAN） is introduced to examine gearbox fault data and a method for condition identification of gearboxes based on CEEMDAN energy entropy is proposed. In the proposed method,the gearbox vibration signal is decomposed by using the CEEMDAN,then the energy entropy of the decomposition results is calculated and the energy entropy is taken as a characteristic parameter to identify different gear operating condition. Afterwards,the proposed method is used to discriminate between normal,slight-scratch and medium-scratch gear operating conditions,and compared with the method based on EMD \ EEMD energy entropy. The results show that the proposed method can effectively discriminate between these three similar gear operating conditions,and the proposed method has a clear advantage in condition identification of gearboxes.
