Research on Application of Blind Source Separation in Rolling Bearing Fault Diagnosis Based on Particle Swarm Optimization

This paper presents blind source separation of rolling bearing based on particle swarm optimization. The algorithm combines the advantages of both blind source separation and particle swarm optimization. Through the experiment it is shown that the algorithm can separate the signals collected from rolling bearing and gearbox effectively, which can provide a new method for fault diagnosis and signal processing of machinery equipment.