A novel method for fault diagnosis for rolling bearing of wind turbine based on combining morphological filter and ensemble empirical mode decomposition（EEMD）is presented.Firstly

de-noising processing of the practical bearing fault signal is carried out by designing open-closing and close-opening combined morphological filter

and then the de-noised signal is decomposed into several intrinsic mode functions（IMFs）via EEMD adaptively.The pseudo-components in EEMD are removed by using the correlation coefficient method.Finally

a more accurate Hilbert-Huang spectrum of IMFs is obtained

and the characteristic frequencies are extracted

then the fault is diagnosed.Experiment results show that the proposed method is effective for extracting fault feature.