Separating for Nonlinear Mixed Rotor Fault Signals Based on Adaptive Particle Swarm Optimization

Abstract

The performance of existing nonlinear mechanical failure signal separation methods is affected by the non-linear contrast function that is selected according to the distribution of original signals. To solve this problem, a blind source separation algorithm based on adaptive particle swarm optimization is proposed, which takes the negentropy of mixtures as a contrast function. The inertia weight factor depends on the negentropy, which can improve the contradiction between the convergence speed and the performance of separated signals. The simulation results verified the effectiveness of the proposed method. Finally, some mixed rotor vibration signals were separated successfully using the proposed method.