Abstract: It is difficult to accurately extract the blade tip-timing pulse signals in the environments with noise interference. In this paper, a noised blade tip-timing pulse signal extracting method based on ensemble empirical mode decomposition (EEMD) was proposed to solve this problem. In this method, non-stationary and non-linear original noised signals are adaptively decomposed by means of EEMD, and a multi-scale low pass filter is constructed for denoising. Secondly, the denoised pulse signals are processed by means of square wave shaping. And thirdly, optimal denoising and shaping evaluation indexes of fusion similarity and correlation are put forward to evaluate the processing results of noised signals. Then, based on the characteristics of noised blade tip-timing pulse signals, a mathematical model was established to verify reliability and applicability of this newly developed method. Finally, the noised blade tip-timing pulse signals after denoising and shaping were compared with the original noiseless signals, and their correlation, similarity and comprehensive evaluation index are above 97%, 89% and 92%, respectively. It is indicated that this EEMD based noised blade tip-timing pulse signal extracting method can accurately extract the blade tip-timing pulse signals in the environments with noise interference, and be beneficial to the development, popularization and application of blade tip-timing technology.