Abstract
Immune theory is applied to independent component analysis in this paper. By elaborated on blind source separation procedure, the blind source separation based on immune optimization algorithm is put forward, that is AIS-ICA algorithm. The paper carried out simulation experiments of mixing and separation for four specific signals. The experimental results show that the convergence speed and separation precision is high, and it has good stability. The new algorithm is used to gearbox vibration signals for blind source separation and fault diagnosis, fault information carried by vibration signals enhanced. Results show that the algorithm used to separate vibration signals of gearbox can greatly enhance fault information, reducing difficulty of gearbox fault diagnosis.
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