Fault Diagnosis of Rolling Bearing Based on Teager Energy Operator and EEMD

As it was difficult to extract weak fault feature of rolling bearings with the method of ensemble empirical mode decomposition (EEMD), a modified EEMD was proposed. First the method of minimum entropy deconvolution (MED) was used to restrain the noise and highlight the impulse components of vibration signals. Second the signals were decomposed into different intrinsic mode function (IMF) by using EEMD, and then the sensitive IMFS were selected and false IMFS were eliminated to reconstructed the new signals. Third the noise components of IMFS were restrained by the method of wavelet-threshold. The power spectrum could be used to obtain the weak fault features by using Teager Energy Operator at last. The diagnosis results with the simulation signals and experimental data of inner race faults, had indicated the effectiveness and accuracy of the method.