To effectively extract the fault features of roller bearings, a new method based on Local Mean Decomposition and slice bispectrum are proposed. Original fault signals were decomposed into a series of product function components of different frequency bands, filter the decomposition results by proposed kurtosis criteria, then select PF component whose kurtosis value is the maximum, the fault type could be judged by analysis the slice bispectrum which is computed for the envelope signal of the product function component. In order to reduce the amount of computation and accelerate the decomposition rate, the stopping conditions of local mean decomposition was improved, then the decomposed capacity of LMD and capabilities of noise suppression and eliminate the non-quadratic phase coupling harmonic components of slice bispectrum were verified by simulation signal .Bearing inner ring and outer ring fault signals were analysis by this diagnostic method and the results show that this method has a certain degree of reliability.