Noise-assisted EMD-1.5 dimension spectrum for signal anti-alias decomposition and feature extraction

To effectively extract the weak fault features of core components of a large-scale power equipment, a new fault diagnosis method based on noise-assisted EMD-1.5 dimension spectrum was proposed. The interval characteristic of signal extreme value points affected the appearance of mode mixing in the EMD method. According to this status, an evaluation method of the interval characteristic of signal extreme value points was proposed, the principle of Gaussian white noise helping to avoid mode mixing was analyzed. The noise-assisted EMD method was obtained by adding Gaussian white noise to the original signal to improve the capability of signal anti-alias decomposition. Meanwhile, the noise assisted EMD method combined with a 1.5 dimension spectrum to get a new fault diagnosis method having the capability of effective anti-alias decomposition and extracting the nonlinear coupling feature in order to extract the weak fault features. Finally, the noise assisted EMD-1.5 dimension spectrum was effectively verified by simulation experiments and engineering examples of electric locomotive rolling bearing fault diagnosis.