Aiming at the modal aliasing problem of the Adaptive Local Iterative Filtering （ALIF） method， a Pseudo-extrema-based Adaptive Local Iterative Filtering （PEALIF） method is proposed， which uses the method of adding pseudo-extrema to make the distribution of signal extremely more uniform， effectively suppressing the problem of modal aliasing， and also ensuring the order of algorithm decomposition. The principle of the PEALIF method is introduced in detail. Simultaneously， simulation signals are constructed， and this method is analyzed and compared with the Empirical Mode Decomposition （EMD）， Ensemble Empirical Mode Decomposition （EEMD）， Complementary Ensemble Empirical Mode Decomposition （CEEMD） and ALIF methods. The results show that PEALIF has certain advantages in decomposition ability， suppression of modal aliasing and anti-noise interference. Finally， this method is applied to the fault diagnosis of double inner ring bearing. The experimental results show that the PEALIF method can obtain more prominent and easily identifiable fault feature information， which confirms the application of this method in the bearing fault diagnosis analysis.